COMPUTERS—THE MACHINES WE THINK WITH






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Computers—


THE MACHINES WE THINK WITH



          D. S. HALACY, JR.








[Illustration]

HARPER & ROW, PUBLISHERS
NEW YORK, EVANSTON, AND LONDON







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COMPUTERS—THE MACHINES WE THINK WITH. _Copyright © 1962, by Daniel S.
Halacy, Jr. Printed in the United States of America. All rights in this
book are reserved. No part of the book may be used or reproduced in any
manner whatsoever without written permission except in the case of brief
quotations embodied in critical articles and reviews. For information
address Harper & Row, Publishers, Incorporated, 49 East 33rd Street, New
York 16, N.Y._



          _Library of Congress catalog card number: 62-14564_

                                  F-S


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                                Contents


             1. Computers—The Machines We Think With        1

             2. The Computer’s Past                        18

             3. How Computers Work                         48

             4. Computer Cousins—Analog and Digital        72

             5. The Binary Boolean Bit                     96

             6. The Electronic Brain                      121

             7. Uncle Sam’s Computers                     147

             8. The Computer in Business and Industry     171

             9. The Computer and Automation               201

            10. The Academic Computer                     219

            11. The Road Ahead                            251


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                  COMPUTERS—THE MACHINES WE THINK WITH






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                       1: Computers—The Machines
                               We Think With


While you are reading this sentence, an electronic computer is
performing 3 million mathematical operations! Before you read this page,
another computer could translate it and several others into a foreign
language. Electronic “brains” are taking over chores that include the
calculation of everything from automobile parking fees to zero hour for
space missile launchings.

Despite bitter winter weather, a recent conference on computers drew
some 4,000 delegates to Washington, D.C.; indicating the importance and
scope of the new industry. The 1962 domestic market for computers and
associated equipment is estimated at just under $3 billion, with more
than 150,000 people employed in manufacture, operation, and maintenance
of the machines.

In the short time since the first electronic computer made its
appearance, these thinking machines have made such fantastic strides in
so many different directions that most of us are unaware how much our
lives are already being affected by them. Banking, for example, employs
complex machines that process checks and handle accounts so much faster
than human bookkeepers that they do more than an hour’s work in less
than thirty seconds.

[Illustration:

  _General Electric Co., Computer Dept._

  Programmer at console of computer used in electronic processing of
    bank checking accounts.
]

Our government is one of the largest users of computers and
“data-processing machines.” The census depends on such equipment, and it
played a part in the development of early mechanical types of computers
when Hollerith invented a punched-card system many years ago. In another
application, the post office uses letter readers that scan addresses and
sort mail at speeds faster than the human eye can keep up with. Many
magazines have put these electronic readers to work whizzing through
mailing lists.

[Illustration:

  _General Electric Co., Computer Dept._

  Numbers across bottom of check are printed in magnetic ink and can be
    read by the computer.
]

In Sweden, writer Astrid Lindgren received additional royalties for one
year of 9,000 _kronor_ because of library loans. Since this was based on
850,000 total loans of her books from thousands of schools and
libraries, the bookkeeping was possible only with an electronic
computer.

Computers are beginning to take over control of factories, steel mills,
bakeries, chemical plants, and even the manufacture of ice cream. In
scientific research, computers are solving mathematical and logical
problems so complex that they would go forever unsolved if men had to do
the work. One of the largest computing systems yet designed,
incorporating half a million transistors and millions of other parts,
handles ticket reservations for the airlines. Others do flight planning
and air traffic control itself.

Gigantic computerized air defense systems like SAGE and NORAD help guard
us from enemy attack. When John Glenn made his space flight, giant
computers on the ground made the vital calculations to bring him safely
back. Tiny computers in space vehicles themselves have proved they can
survive the shocks of launching and the environment of space. These
airborne computers make possible the operation of Polaris, Atlas, and
Minuteman missiles. Such applications are indicative of the scope of
computer technology today; the ground-based machines are huge, taking up
rooms and even entire buildings while those tailored for missiles may
fit in the palm of the hand. One current military project is such an
airborne computer, the size of a pack of cigarettes yet able to perform
thousands of mathematical and logical operations a second.

Computers are a vital part of automation, and already they are running
production lines and railroads, making mechanical drawings and weather
predictions, and figuring statistics for insurance companies as well as
odds for gamblers. Electronic machines permit the blind to read a page
of ordinary type, and also control material patterns in knitting mills.
This last use is of particular interest since it represents almost a
full circle in computer science. Oddly, it was the loom that inspired
the first punched cards invented and used to good advantage by the
French designer Jacquard. These homely forerunners of stored information
sparked the science that now returns to control the mills.

Men very wisely are now letting computers design other computers, and in
one recent project a Bell Laboratories computer did a job in twenty-five
minutes that would have taken a human designer a month. Even more
challenging are the modern-day “robots” performing precision operations
in industrial plants. One such, called “Unimate,” is simply guided
through the mechanical operations one time, and can then handle the job
alone. “TransfeRobot 200” is already doing assembly-line work in dozens
of plants.

The hope has been expressed that computer extension of our brainpower by
a thousandfold would give our country a lead over potential enemies.
This is a rather vain hope, since the United States has no corner on the
computer market. There is worldwide interest in computers, and machines
are being built in Russia, England, France, Germany, Switzerland,
Holland, Sweden, Africa, Japan, and other countries. A remarkable
computer in Japan recognizes 8,000 colors and analyzes them instantly.
Computer translation from one language to another has been mentioned,
and work is even being done on machines that will permit us to speak
English into a phone in this country and have it come out French, or
whatever we will, overseas! Of course, computers have a terminology all
their own too; words like analog and digital, memory cores, clock rates,
and so on.

The broad application of computers has been called the “second
industrial revolution.” What the steam engine did for muscles, the
modern computer is beginning to do for our brains. In their slow climb
from caveman days, humans have encountered ever more problems; one of
the biggest of these problems eventually came to be merely how to solve
all the other problems.

At first man counted on his fingers, and then his toes. As the problems
grew in size, he used pebbles and sticks, and finally beads. These
became the abacus, a clever calculating device still in constant use in
many parts of the world. Only now, with the advent of low-cost
computers, are the Japanese turning from the _soroban_, their version of
the abacus.

The large-scale computers we are becoming familiar with are not really
as new as they seem. An Englishman named Babbage built what he called
a “difference engine” way back in 1831. This complex mechanical
computer cost a huge sum even by today’s standards, and although it
was never completed to Babbage’s satisfaction, it was the forerunner
and model for the successful large computers that began to appear a
hundred years later. In the meantime, of course, electronics has come
to the aid of the designer. Today, computer switches operate at
billionths-of-a-second speeds and thus make possible the rapid
handling of quantities of work like the 14 billion checks we
Americans wrote in 1961.

There are dozens of companies now in the computer manufacturing field,
producing a variety of machines ranging in price from less than a
hundred dollars total price to rental fees of $100,000 a month or more.
Even at these higher prices the big problem of some manufacturers is to
keep up with demand. A $1 billion market in 1960, the computer field is
predicted to climb to $5 billion by 1965, and after that it is anyone’s
guess. Thus far all expert predictions have proved extremely
conservative.

The path of computer progress is not always smooth. Recently a computer
which had been installed on a toll road to calculate charges was so
badly treated by motorists it had to be removed. Another unfortunate
occurrence happened on Wall Street. A clever man juggled the controls of
a large computer used in stock-market work and “made” himself a quarter
of a million dollars, though he ultimately landed in jail for his
illegal computer button pushing. Interestingly, there is one corrective
institution which already offers a course in computer engineering for
its inmates.

So great is the impact of computers that lawyers recently met for a
three-day conference on the legal aspects of the new machines. Points
taken up included: Can business records on magnetic tape or other
storage media be used as evidence? Can companies be charged with
mismanagement for not using computers in their business? How can
confidential material be handled satisfactorily on computers?

Along with computing machines a whole new technology is growing.
Universities and colleges—even high schools—are teaching courses in
computers. And the computer itself is getting into the teaching business
too. The “teaching machine” is one of the most challenging computer
developments to come along so far. These mechanical professors range
from simple “programmed” notebooks, such as the Book of Knowledge and
Encyclopedia Britannica are experimenting with, to complex computerized
systems such as that developed by U.S. Industries, Inc., for the Air
Force and others.

The computer as a teaching machine immediately raises the question of
intelligence, and whether or not the computer has any. Debate waxes hot
on this subject; but perhaps one authority was only half joking when he
said that the computer designer’s competition was a unit about the size
of a grapefruit, using only a tenth of a volt of electricity, with a
memory 10,000 times as extensive as any existing electronic computer.
This is a brief description of the human brain, of course.

When the first computers appeared, those like ENIAC and BINAC, fiction
writers and even some science writers had a field day turning the
machines into diabolical “brains.” Whether or not the computer really
thinks remains a controversial question. Some top scientists claim that
the computer will eventually be far smarter than its human builder;
equally reputable authorities are just as sure that no computer will
ever have an original thought in its head. Perhaps a safe middle road is
expressed with the title of this book; namely that the machine is simply
an extension of the human brain. A high-speed abacus or slide rule, if
you will; accurate and foolproof, but a moron nonetheless.

There are some interesting machine-brain parallels, of course. Besides
its ability to do mathematics, the computer can perform logical
reasoning and even make decisions. It can read and translate;
remembering is a basic part of its function. Scientists are now even
talking of making computers “dream” in an attempt to come up with new
ideas!

More similarities are being discovered or suggested. For instance, the
interconnections in a computer are being compared with, and even crudely
patterned after, the brain’s neurons. A new scientific discipline,
called “bionics,” concerns itself with such studies. Far from being a
one-way street, bionics works both ways so that engineers and biologists
alike benefit. In fact, some new courses being taught in universities
are designed to “bridge the gap between engineering and biology.”

At one time the only learning a computer had was “soldered in”; today
the machines are being “forced” to learn by the application of
punishment or reward as necessary. “Free” learning in computers of the
Perceptron class is being experimented with. These studies, and
statements like those of renowned scientist Linus Pauling that he
expects a “molecular theory” of learning in human beings to be
developed, are food for thought as we consider the parallels our
electronic machines share with us. Psychologists at the University of
London foresee computers not only training humans, but actually watching
over them and predicting imminent nervous breakdowns in their charges!

[Illustration:

  _Cornell Aeronautical Laboratory_

  Bank of “association” units in Mark I Perceptron, a machine that
    “learns” from experience.
]

To demonstrate their skill many computers play games of tick-tack-toe,
checkers, chess, Nim, and the like. A simple electromechanical computer
designed for young people to build can be programmed to play
tick-tack-toe expertly. Checker- and chess-playing computers are more
sophisticated, many of them learning as they play and capable of an
occasional move classed as brilliant by expert human players. The IBM
704 computer has been programmed to inspect the results of its possible
decisions several moves ahead and to select the best choice. At the end
of the game it prints out the winner and thanks its opponent for the
game. Rated as polite, but only an indifferent player by experts, the
computer is much like the checker-playing dog whose master scoffed at
him for getting beaten three games out of five. Chess may well be an
ultimate challenge for any kind of brain, since the fastest computer in
operation today could not possibly work out all the possible moves in a
game during a human lifetime!

As evidenced in the science-fiction treatment early machines got, the
first computers were monsters at least in size. Pioneering design
efforts on machines with the capacity of the brain led to plans for
something roughly the size of the Pentagon, equipped with its own
Niagara for power and cooling, and a price tag the world couldn’t
afford. As often seems to happen when a need arises, though, new
developments have come along to offset the initial obstacles of size and
cost.

One such development was the transistor and other semiconductor devices.
Tiny and rugged, these components require little power. With the old
vacuum-tubes replaced, computers shrank immediately and dramatically. On
the heels of this micro-miniaturization have come new and even smaller
devices called “ferrite cores” and “cryotrons” using magnetism and
supercold temperatures instead of conventional electronic techniques.

As a result, an amazing number of parts can be packed into a tiny
volume. So-called “molecular electronics” now seems to be a possibility,
and designers of computers have a gleam in their eyes as they consider
progress being made toward matching the “packaging density” of the
brain. This human computer has an estimated 100 billion parts per cubic
foot!

We have talked of reading and translating. Some new computers can also
accept voice commands and speak themselves. Others furnish information
in typed or printed form, punched cards, or a display on a tube or
screen.

Like us, the computer can be frustrated by a task beyond its
capabilities. A wrong command can set its parts clicking rapidly but in
futile circles. Early computers, for example, could be panicked by the
order to divide a number by zero. The solution to that problem of course
is infinity, and the poor machine had a hard time trying to make such an
answer good.

[Illustration:

  _Aeronutronic Division, Ford Motor Co._

  This printed-circuit card contains more than 300 BIAX memory elements.
    Multiples of such cards mounted in computers store large amounts of
    information.
]

There are other, quainter stories like that of the pioneer General
Electric computer that simply could not function in the dark. All day
long it hummed efficiently, but problems left with it overnight came out
horribly botched for no reason that engineers could discover. At last it
was found that a light had to be left burning with the scary machine!
Neon bulbs in the computer were enough affected by light and darkness
that the delicate electronic balance of the machine had been upset.

Among the computer’s unusual talents is the ability to compose music.
Such music has been published and is of a quality to give rise to
thoughtful speculation that perhaps great composers are simply good
selectors of music. In other words, all the combinations of notes and
meter exist: the composer just picks the right ones. No less an
authority than Aaron Copland suggests that “we’ll get our new music by
feeding information into an electronic computer.” Not content with
merely writing music, some computers can even play a tune. At Christmas
time, carols are rendered by computers specially programmed for the
task. The result is not unlike a melody played on a pipe organ.

In an interesting switch of this musical ability on the part of the
machine, Russian engineers check the reliability of their computers by
having them memorize Mozart and Grieg. Each part of the complex machines
is assigned a definite musical value, and when the composition is
“played back” by the computer, the engineer can spot any defects
existing in its circuitry. Such computer maintenance would seem to be an
ideal field for the music lover.

In a playful mood, computers match pennies with visitors, explain their
inner workings as they whiz through complex mathematics, and are even
capable of what is called heuristic reasoning. This amounts to playing
hunches to reach short-cut solutions to otherwise unsolvable problems. A
Rand Corporation computer named JOHNNIAC demonstrated this recently. It
was given some basic axioms and asked to prove some theorems. JOHNNIAC
came up with the answers, and in one case produced a proof that was
simpler than that given in the text. As one scientist puts it, “If
computers don’t really think, they at least put on a pretty creditable
imitation of the real thing.”

Computers are here to stay; this has been established beyond doubt. The
only question remaining is how fast the predictions made by dreamers and
science-fiction writers—and now by sober scientists—will come to be a
reality. When we consider that in the few years since the 1953 crop of
computers, their capacity and speed has been increased more than
fiftyfold, and is expected to jump another thousandfold in two years,
these dreams begin to sound more and more plausible.

One quite probable use for computers is medical diagnosis and
prescription of treatment. Electronic equipment can already monitor an
ailing patient, and send an alarm when help is needed. We may one day
see computers with a built-in bedside manner aiding the family doctor.

The accomplished inroads of computing machines in business are as
nothing to what will eventually take place. Already computer
“game-playing” has extended to business management, and serious
executives participate to improve their administrative ability. We speak
of decision-making machines; business decisions are logical applications
for this ability. Computers have been given the job of evaluating
personnel and assigning salaries on a strictly logical basis. Perhaps
this is why in surveys questioning increased use of the machines, each
executive level in general tends to rate the machine’s ability just
below its own.

Other games played by the computer are war games, and computers like
SAGE are well known. This system not only monitors all air activity but
also makes decisions, assigns targets, and then even flies the
interceptor planes and guided missiles on their missions. Again in the
sky, the increase of commercial air traffic has perhaps reached the
limit of human ability to control it. Computers are beginning to take
over here too, planning flights and literally flying the planes.

Surface transport can also be computer-controlled. Railroads are
beginning to use the computer techniques, and automatic highways are
inevitable. Ships also benefit, and special systems coupled to radar can
predict courses and take corrective action when necessary.

Men seem to have temporarily given up trying to control the weather, but
using computers, meteorologists can take the huge mass of data from all
over the world and make predictions rapidly enough to be of use.

We have talked of the computer’s giant strides in banking. Its wide use
in stores is not far off. An English computer firm has designed an
automatic supermarket that assembles ordered items, prices them, and
delivers them to the check stand. At the same time it keeps a running
inventory, price record, and profit and loss statement, besides billing
the customer with periodic statements. The storekeeper will have only to
wash the windows and pay his electric power bill.

Even trading stamps may be superseded by computer techniques that keep
track of customer purchases and credit him with premiums as he earns
them. Credit cards have helped pioneer computer use in billing; it is
not farfetched to foresee the day when we are issued a lifetime,
all-inclusive credit card—perhaps with our birth certificate!—a card
with our thumbprint on it, that will buy our food, pay our rent and
utilities and other bills. A central computer system will balance our
expenses against deposits and from time to time let us know how we stand
financially.

As with many other important inventions, the computer and its technology
were spurred by war and are aided now by continuing threats of war. It
is therefore pleasant to think on the possibilities of a computer system
“programmed” for peace: a gigantic, worldwide system whose input
includes all recorded history of all nations, all economic and cultural
data, all weather information and other scientific knowledge. The output
of such a machine hopefully would be a “best plan” for all of us. Such a
computer would have no ax to grind and no selfish interests unless they
were fed into it.

Given all the facts, it would punch out for us a set of instructions
that would guarantee us the best life possible. This has long been a
dream of science writers. H. G. Wells was one of these, suggesting a
world clearinghouse of information in his book _World Brain_ written in
the thirties. In this country, scientist Vannevar Bush suggested a
similar computer called “Memex” which could store huge amounts of data
and answer questions put to it.

The huge amounts of information—books, articles, speeches, and records
of all sorts—are beginning to make it absolutely necessary for an
efficient information retrieval system. Many cases have been noted in
which much time and effort are spent on a project which has already been
completed but then has become lost in the welter of literature crammed
into libraries. The computer is a logical device for such work; in a
recent test such a machine scored 86 per cent in its efforts to locate
specific data on file. Trained workers rated only 38 per cent in the
same test!

[Illustration:

  _The Boeing Co._

  Engineers using computers to solve complex problems in aircraft
    design.
]

The science of communication is advancing along with that of computers,
and can help make the dream of a worldwide “brain” come true. Computers
in distant cities are now linked by telephone lines or radio, and
high-speed techniques permit the transmission of many thousands of words
per _second_ across these “data links.” An interesting sidelight is the
fact that an ailing computer can be hooked by telephone line with a
repair center many miles away and its ailments diagnosed by remote
control. Communications satellites that are soon to be dotting the sky
like tiny moons may well play a big part in computing systems of the
future. Global weather prediction and worldwide coordination of trade
immediately come to mind.

While we envision such far-reaching applications, let’s not lose sight
of the possibilities for computer use closer to home—right in our homes,
as a matter of fact. Just as early inventors of mechanical power devices
did not foresee the day when electric drills and saws for hobbyist would
be commonplace and the gasoline engine would do such everyday chores as
cutting the grass in our yards, the makers of computers today cannot
predict how far the computer will go in this direction. Perhaps we may
one day buy a “Little Dandy Electro-Brain” and plug it into the wall
socket for solving many of the everyday problems we now often guess
wrong on.

[Illustration:

  _Royal McBee Corp._

  Students at Staples High School, Westport, Connecticut, attend a
    summer session to learn the techniques of programming and operating
    an electronic computer.
]

[Illustration:

  _The Saturday Evening Post_

  “Herbert’s been replaced by an electronic brain—one of the simpler
    types.”
]

Some years ago a group of experts predicted that by 1967 the world
champion chess player would be an electronic computer. No one has yet
claimed that we would have a president of metal and wire, but some
interesting signposts are being put up. Computers are now used widely to
predict the result of elections. Computers count the votes, and some
have suggested that computers could make it possible for us to vote at
home. The government is investigating the effectiveness of a
decision-making computer as a stand-by aid for the President in this
complex age we are moving into. No man has the ability to weigh every
factor and to make decisions affecting the world. Perhaps a computer can
serve in an advisory capacity to a president or to a World Council;
perhaps—

It is comforting to remember that men will always tell the computer what
it is supposed to do. No computer will ever run the world any more than
the cotton gin or the steam engine or television runs the world. And in
an emergency, we can always pull out the wallplug, can’t we?


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    “_History is but the unrolled scroll of prophecy._”

                    —James A. Garfield




                         2: The Computer’s Past


Although it seemed to burst upon us suddenly, the jet airplane can trace
its beginnings back through the fabric wings of the Wrights to the wax
wings of Icarus and Daedalus, and the steam aerophile of Hero in ancient
Greece. The same thing is true of the computer, the “thinking machine”
we are just now becoming uncomfortably aware of. No brash upstart, it
has a long and honorable history.

Naturalists tell us that man is not the only animal that counts. Birds,
particularly, also have an idea of numbers. Birds, incidentally, use
tools too. We seem to have done more with the discoveries than our
feathered friends; at least no one has yet observed a robin with a slide
rule or a snowy egret punching the controls of an electronic digital
computer. However, the very notion of mere birds being tool and number
users does give us an idea of the antiquity and lengthy heritage of the
computer.

The computer was inevitable when man first began to make his own
problems. When he lived as an animal, life was far simpler, and all he
had to worry about was finding game and plants to eat, and keeping from
being eaten or otherwise killed himself. But when he began to dabble in
agriculture and the raising of flocks, when he began to think
consciously and to reflect about things, man needed help.

First came the hand tools that made him more powerful, the spears and
bows and arrows and clubs that killed game and enemies. Then came the
tools to aid his waking brain. Some 25,000 years ago, man began to
count. This was no mean achievement, the dim, foggy dawning of the
concept of number, perhaps in the caves in Europe where the walls have
been found marked with realistic drawings of bison. Some budding
mathematical genius in a skin garment only slightly shaggier than his
mop of hair stared blinking at the drawings of two animals and then
dropped his gaze to his two hands. A crude, tentative connection jelled
in his inchoate gray matter and he shook his head as if it hurt. It was
enough to hurt, this discovery of “number,” and perhaps this particular
pioneer never again put two and two together. But others did; if not
that year, the next.

Armed with his grasp of numbers, man didn’t need to draw two mastodons,
or sheep, or whatever. Two pebbles would do, or two leaves or two
sticks. He could count his children on his fingers—we retain the
expression “a handful” to this day, though often our children are
another sort of handful. Of course, the caveman did not of a sudden do
sums and multiplications. When he began to write, perhaps 5,000 years
later, he had formed the concept of “one,” “two,” “several,” and “many.”

Besides counting his flock and his children, and the number of the
enemy, man had need for counting in another way. There were the seasons
of the year, and a farmer or breeder had to have a way of reckoning the
approach of new life. His calendar may well have been the first
mathematical device sophisticated enough to be called a computer.

It was natural that numbers be associated with sex. The calendar was
related to the seasons and the bearing of young. The number three, for
example, took on mystic and potent connotation, representing as it did
man’s genitals. Indeed, numbers themselves came quaintly to have sex.
One, three, and the other odd numbers were male; the symmetrical, even
numbers logically were female.

The notion that man used the decimal system because of his ten fingers
and toes is general, but it was some time before this refinement took
place. Some early peoples clung to a simpler system with a base of only
two; and interestingly a tribe of Australian aborigines counts today
thus: _enea_ (1), _petchaval_ (2), _enea petchaval_ (3), _petchaval
petchaval_ (4). Before we look down our noses at this naïve system, let
us consider that high-speed electronic computers use only two values, 1
and 0.

But slowly symbols evolved for more and more numbers, numbers that at
first were fingers, and then perhaps knots tied in a strip of hide. This
crude counting aid persists today, and cowboys sometimes keep rough
tallies of a herd by knotting a string for every five that pass. Somehow
numbers took on other meanings, like those that figure in courtship in
certain Nigerian tribes. In their language, the number six also means “I
love you.” If the African belle is of a mind when her boyfriend tenderly
murmurs the magic number, she replies in like tone, “Eight!”, which
means “I feel the same way!”

From the dawn of history there have apparently been two classes of us
human beings, the “haves” and the “have nots.” Nowadays we get bills or
statements from our creditors; in early days, when a slate or clay
tablet was the document, a forerunner of the carbon copy or duplicate
paper developed. Tallies were marked for the amount of the debt, the
clay tablet was broken across the marks, and creditor and debtor each
took half. No chance for cheating, since a broken half would fit only
the proper mate!

Numbers at first applied only to discrete, or distinctly separate,
things. The scratches on a calendar, the tallies signifying the count of
a flock; these were more easily reckoned. The idea of another kind of
number inspired the first clocks. Here was a monumental breakthrough in
mathematics. Nature provided the sunrise that clearly marked the
beginning of each day; man himself thought to break the day into
“hours,” or parts of the whole. Such a division led eventually to
measurement of size and weight. Now early man knew not only how many
goats he had, but how many “hands” high they were, and how many “stones”
they weighed. This further division ordained another kind of mechanical
computer man must someday contrive—the analog.

The first counting machines used were pebbles or sea shells. For the
Stone Age businessman to carry around a handful of rocks for all his
transactions was at times awkward, and big deals may well have gone
unconsummated for want of a stone. Then some genius hit on the idea of
stringing shells on a bit of reed or hide; or more probably the necklace
came first as adornment and the utilitarian spotted it after this style
note had been added. At any rate, the portable adding machine became
available and our early day accountant grew adroit at sliding the beads
back and forth on the string. From here it was only a small step, taken
perhaps as early as 3000 B.C., to the rigid counter known as the abacus.

The word “counter” is one we use in everyday conversation. We buy stock
over the counter; some deals are under the counter. We all know what the
counter itself is—that wide board that holds the cash register and
separates us from the shopkeeper. At one time the cash register _was_
the counter; actually the counting board had rods of beads like the
abacus, or at least grooves in which beads could be moved. The totting
up of a transaction was done on the “counter”; it is still there
although we have forgotten whence came its name.

The most successful computer used for the next 5,000 years, the portable
counter, or the abacus, is a masterpiece of simplicity and
effectiveness. Though only a frame with several rows of beads, it is
sophisticated enough that as late as 1947 Kiyoshi Matsuzake of the
Japanese Ministry of Communications, armed with the Japanese version—a
_soroban_, bested Private Tom Wood of the U. S. Army of Occupation
punching the keys of an up-to-the-minute electric calculating machine in
four of five problem categories! Only recently have Japanese banks gone
over to modern calculators, and shopkeepers there and in other lands
still conduct business by this rule of thumb and forefinger.

[Illustration:

  The abacus, ancient mechanical computer, is still in use in many parts
    of the world. Here is the Japanese version, the _soroban_, with
    problem being set up.
]

The name abacus comes to us by way of the Greek _abax_, meaning “dust.”
Scholars infer that early sums were done schoolboy fashion in Greece
with a stylus on a dusty slate, and that the word was carried over to
the mechanical counter. The design has changed but little over the years
and all abacuses bear a resemblance. The major difference is the number
of beads on each row, determined by the mathematical base used in the
particular country. Some in India, for example, were set up to handle
pounds and shillings for use in shops. Others have a base of twelve. The
majority, however, use the decimal system. Each row has seven beads,
with a runner separating one or two beads from the others. Some systems
use two beads on the narrow side, some only one; this is a mathematical
consideration with political implications, incidentally: The Japanese
_soroban_ has the single-bead design; Korea’s _son pan_ uses two. When
Japan took over Korea the two-bead models were tabu, and went out of use
until the Koreans were later able to win their independence again.

About the only thing added to the ancient abacus in recent years is a
movable arrow for marking the decimal point. W. D. Loy patented such a
gadget in the United States. Today the abacus remains a useful device,
not only for business, but also for the teaching of mathematics to
youngsters, who can literally “grasp their numbers.” For that reason it
ought also to be helpful to the blind, and as a therapeutic aid for
manual dexterity. Apparently caught up in the trend toward smaller
computers, the abacus has been miniaturized to the extent that it can be
worn as earrings or on a key chain.

Even with mechanical counters, early mathematicians needed written
numbers. The caveman’s straight-line scratches gave way to
hieroglyphics, to the Sumerian cuneiform “wedges,” to Roman numerals,
and finally to Hindu and Arabic. Until the numbers, 1, 2, 3, 4, 5, 6, 7,
8, 9, and that most wonderful of all, 0 or zero, computations of any but
the simplest type were apt to be laborious and time-consuming. Even
though the Romans and Greeks had evolved a decimal system, their
numbering was complex. To count to 999 in Greek required not ten numbers
but twenty-seven. The Roman number for 888 was DCCCLXXXVIII. Multiplying
CCXVII times XXIX yielded an answer of MMMMMMCCXCIII, to be sure, but
not without some difficulty. It required an abacus to do any kind of
multiplication or division.

Indeed, it was perhaps from the abacus that the clue to Arabic
simplicity came. The Babylonians, antedating the Greeks, had
nevertheless gone them one better in arithmetic by using a “place”
system. In other words, the position of a number denoted its value. The
Babylonians simply left an empty space between cuneiform number symbols
to show an empty space in this positional system. Sometime prior to 300
B.C. a clever mathematician tired of losing track and punched a dot in
his clay tablet to fill the empty space and avoid possible error.

The abacus shows these empty spaces on its rows of beads, too, and
finally the Hindus combined their nine numerals with a “dot with a hole
in it” and gave the mathematical world the zero. In Hindu it was _sifr_,
corrupted to _zephirium_ in Latin, and gives us today both cipher and
zero. This enigma of nothingness would one day be used by Leibnitz to
prove that God made the world; it would later become half the input of
the electronic computer! Meantime, it was developed independently in
various other parts of the world; the ancient Mayans being one example.

Impressed as we may be by an electronic computer, it may take some
charity to recognize its forebears in the scratchings on a rock. To call
the calendar a computer, we must in honesty add a qualifying term like
“passive.” The same applies to the abacus despite its movable counters.
But time, which produced the simple calendar, also furnished the
incentive for the first “active” computers too. The hourglass is a
primitive example, as is the sundial. Both had an input, a power source,
and a readout. The clock interestingly ended up with not a decimal
scheme, but one with a base of twelve. Early astronomers began
conventionally bunching days into groups of ten, and located different
stars on the horizon to mark the passage of the ten days. It was but a
step from here to use these “decans,” as they were called, to further
divide each night itself into segments. It turned out that 12 decans did
the trick, and since symmetry was a virtue the daylight was similarly
divided by twelve, giving us a day of 24 hours rather than 10 or 20.

From the simple hourglass and the more complex water clocks, the Greeks
progressed to some truly remarkable celestial motion computers. One of
these, built almost a hundred years before the birth of Christ, was
recently found on the sea bottom off the Greek island of Antikythera. It
had been aboard a ship which sank, and its discovery came as a surprise
to scholars since history recorded no such complex devices for that era.
The salvaged Greek computer was designed for astronomical work, showing
locations of stars, predicting eclipses, and describing various cycles
of heavenly bodies. Composed of dozens of gears, shafts, slip rings, and
accurately inscribed plates, it was a computer in the best sense of the
word and was not exceeded technically for many centuries.

The Greek engineer Vitruvius made an interesting observation when he
said, “All machinery is generated by Nature and the revolution of the
universe guides and controls. Our fathers took precedents from
Nature—developed the comforts of life by their inventions. They rendered
some things more convenient by machines and their revolutions.”
Hindsight and language being what they are, today we can make a nice
play on the word “revolution” as applied to the machine. The Antikythera
computer was a prime example of what Vitruvius was talking about.
Astronomy was such a complicated business that it was far simpler to
make a model of the many motions rather than diagram them or try to
retain them in his mind.

There were, of course, some die-hard classicists who decried the use of
machines to do the work of pure reasoning. Archytas, who probably
invented the screw—or at least discovered its mechanical
principle—attempted to apply such mechanical devices to the solving of
geometrical problems. For this he was taken to task by purist Plato who
sought to preserve the distinct division between “mind” and “machine.”

Yet the syllogistic philosophers themselves, with their major premise,
minor premise, and conclusion, were unwittingly setting the stage for a
different kind of computer—the logic machine. Plato would be horrified
today to see crude decks of cards, or simple electromechanical
contrivances, solving problems of “reason” far faster than he could; in
fact, as fast as the conditions could be set into them!


------------------------------------------------------------------------


                       _The Mechanics of Reason_

Aristotle fathered the syllogism, or at least was first to investigate
it rigorously. He defined it as a formal argument in which the
conclusion follows logically from the premises. There are four common
statements of this type:

                            All S (for is P (for
                              subject) predicate)

                    No S (for subject) is P

                           Some S (for is P
                              subject)

                           Some S (for is not P
                              subject)

Thus, Aristotle might say “All men are mortal” or “No men are immortal”
as his subject. Adding an M (middle term), “Aristotle is a man,” as a
minor premise, he could logically go on and conclude “Aristotle, being a
man, is thus mortal.” Of course the syllogism unwisely used, as it often
is, can lead to some ridiculously silly answers. “All tables have four
legs. Two men have four legs. Thus, two men equal a table.”

Despite the weaknesses of the syllogism, nevertheless it led eventually
to the science of symbolic logic. The pathway was circuitous, even
devious at times, but slowly the idea of putting thought down as letters
or numbers to be logically manipulated to reach proper conclusions
gained force and credence. While the Greeks did not have the final say,
they did have words for the subject as they did for nearly everything
else.

Let us leave the subject of pure logic for a moment and talk of another
kind of computing machine, that of the mechanical doer of work. In the
_Iliad_, Homer has Hephaestus, the god of natural fire and metalworking,
construct twenty three-wheeled chariots which propel themselves to and
fro bringing back messages and instructions from the councils of the
gods. These early automatons boasted pure gold wheels, and handles of
“curious cunning.”

Man has apparently been a lazy cuss from the start and began straightway
to dream of mechanical servants to do his chores. In an age of magic and
fear of the supernatural his dreams were fraught with such machines that
turned into evil monsters. The Hebrew “golem” was made in the shape of
man, but without a soul, and often got out of hand. Literature has
perpetuated the idea of machines running amok, as the broom in “The
Sorcerer’s Apprentice,” but there have been benevolent machines too.
Tik-Tok, a latter-day windup man in _The Road to Oz_, could think and
talk and do many other things men could do. He was not alive, of course,
but he had the saving grace of always doing just what he “was wound up
to do.”

Having touched on the subject of mechanical men, let us now return to
mechanical logic. Since the Greeks, many men have traveled the road of
reason, but some stand out more brightly, more colorfully, than others.
Such a standout was the Spanish monk Ramón Lull. Lull was born in 1232.
A court page, he rose in influence, married young, and had two children,
but did not settle down to married domesticity. A wildly reckless
romantic, he was given to such stunts as galloping his horse into church
in pursuit of some lady who caught his eye. One such escapade led to a
remorseful re-examination of himself, and dramatic conversion to
Christianity.

He began to write books in conventional praise of Christ, but early in
his writings a preoccupation with numbers appears. His _Book of
Contemplation_, for example, actually contains five books for the five
wounds of the Saviour, and forty subdivisions for the days He spent in
the wilderness. There are 365 chapters for daily reading, plus one for
reading only in leap years! Each chapter has ten paragraphs, symbolizing
the ten commandments, and three parts to each chapter. These multiplied
give thirty, for the pieces of silver. Beside religious and mystical
connotations, geometric terms are also used, and one interesting device
is the symbolizing of words and even phrases by letters. This ties in
neatly with syllogism. A sample follows:

… diversity is shown in the demonstration that the D makes of the E and
the F and the G with the I and the K, therefore the H has certain
scientific knowledge of Thy holy and glorious Trinity.

This was only prologue to the _Ars Magna_, the “Great Art” of Ramón
Lull. In 1274, the devout pilgrim climbed Mount Palma in search of
divine help in his writings. The result was the first recorded attempt
to use diagrams to discover and to prove non-mathematical truths.
Specifically, Lull determined that he could construct mechanical devices
that would perform logic to prove the validity of God’s word. Where
force, in the shape of the Crusades, had failed, Lull was convinced that
logical argument would win over the infidels, and he devoted his life to
the task.

Renouncing his estate, including his wife and children, Lull devoted
himself thenceforth solely to his Great Art. As a result of dreams he
had on Mount Palma, the basis for this work was the assumption of simple
premises or principles that are unquestionable. Lull arranged these
premises on rotating concentric circles. The first of these wheels of
logic was called A, standing for God. Arranged about the circumference
of the wheel were sixteen other letters symbolizing attributes of God.
The outer wheel also contained these letters. Rotating them produced 240
two-term combinations telling many things about God and His good. Other
wheels prepared sermons, advised physicians and scientists, and even
tackled such stumpers as “Where does the flame go when the candle is put
out?”

[Illustration:

  From the _Enciclopedia universal illustrada_,
  Barcelona, 1923

  Lull’s wheel.
]

Unfortunately for Lull, even divine help did not guarantee him success.
He was stoned to death by infidels in Bugia, Africa, at the age of
eighty-three. All his wheelspinning logic was to no avail in advancing
the cause of Christianity there, and most mathematicians since have
scoffed at his naïve devices as having no real merit. Far from accepting
the _Ars Magna_, most scholars have been “Lulled into a secure sense of
falsity,” finding it as specious as indiscriminate syllogism.

Yet Lull did leave his mark, and many copies of his wheels have been
made and found useful. Where various permutations of numbers or other
symbols are required, such a mechanical tool is often the fastest way of
pairing them up. Even in the field of writing, a Lullian device was
popular a few decades ago in the form of the “Plot Genii.” With this
gadget the would-be author merely spun the wheels to match up various
characters with interesting situations to arrive at story ideas. Other
versions use cards to do the same job, and one called Plotto was used by
its inventor William Wallace Cook to plot countless stories. Although
these were perhaps not ideas for great literature, eager writers paid as
much as $75 for the plot boiler.

Not all serious thinkers relegated Lull to the position of fanatic
dreamer and gadgeteer. No less a mind that Gottfried Wilhelm von
Leibnitz found much to laud in Lull’s works. The _Ars Magna_ might well
lead to a universal “algebra” of all knowledge, thought Leibnitz. “If
controversies were to arise,” he then mused, “there would be no more
reason for philosophers to dispute than there would for accountants!”

Leibnitz applied Lull’s work to formal logic, constructed tables of
syllogisms from which he eliminated the false, and carried the work of
the “gifted crank” at bit nearer to true symbolic logic. Leibnitz also
extended the circle idea to that of overlapping them in early attempts
at logical manipulation that foreshadowed the work that John Venn would
do later. Leibnitz also saw in numbers a powerful argument for the
existence of God. God, he saw as the numeral 1, and 0 was the
nothingness from which He created the world. There are those, including
Voltaire whose _Candide_ satirized the notion, who question that it is
the best of all possible worlds, but none can question that in the
seventeenth century Leibnitz foresaw the coming power of the binary
system. He also built arithmetical computers that could add and
subtract, multiply and divide.

A few years earlier than Leibnitz, Blaise Pascal was also interested in
computing machines. As a teen-ager working in his father’s tax office,
Pascal wearied of adding the tedious figures so he built himself a
gear-driven computer that would add eight columns of numbers. A tall
figure in the scientific world, Pascal had fathered projective geometry
at age sixteen and later established hydrodynamics as a science. To
assist a gambler friend, he also developed the theory of probability
which led to statistical science.

Another mathematical innovation of the century was that of placing
logarithms on a stick by the Scot, John Napier. What he had done, of
course, was to make an analog, or scale model of the arithmetical
numbers. “Napier’s bones” quickly became what we now call slide rules,
forerunners of a whole class of analog computers that solve problems by
being actual models of size or quantity. Newton joined Leibnitz in
contributing another valuable tool that would be used in the computer,
that of the calculus.


                      _The Computer in Literature_

Even as Plato had viewed with suspicion the infringement of mechanical
devices on man’s domain of higher thought, other men have continued to
eye the growth of “mechanisms” with mounting alarm. The scientist and
inventor battled not merely technical difficulties, but the scornful
satire and righteous condemnation of some of their fellow men. Jonathan
Swift, the Irish satirist who took a swipe at many things that did not
set well with his views, lambasted the computing machine as a substitute
for the brain. In Chapter V, Book Three, of _Gulliver’s Travels_, the
good dean runs up against a scheming scientist in Laputa:

The first Professor I saw was in a very large Room, with Forty Pupils
about him. After Salutation, observing me to look earnestly upon a
Frame, which took up the greatest part of both the Length and Breadth of
the Room; he said, perhaps I might wonder to see him employed in a
Project for improving speculative knowledge by practical and mechanical
Operations. But the World would soon be sensible of its Usefulness; and
he flattered himself, that a more noble exalted Thought never sprang in
any other Man’s Head. Every one knew how laborious the usual Method is
of attaining to Arts and Sciences; whereas by his Contrivance, the most
ignorant Person at a reasonable Charge, and with a little bodily Labour,
may write Books in Philosophy, Poetry, Politicks, Law, Mathematicks, and
Theology, without the least Assistance from Genius or Study. He then led
me to the Frame, about the Sides whereof all his Pupils stood in Ranks.
It was a Twenty Foot Square, placed in the Middle of the Room. The
Superfices was composed of several Bits of Wood, about the Bigness of a
Dye, but some larger than others. They were all linked together by
slender Wires. These Bits of Wood were covered on every Square with
Papers pasted on them; and on these Papers were written all the Words of
their Language in their several Moods, Tenses, and Declensions, but
without any Order. The Professor then desired me to observe, for he was
going to set his Engine to work. The Pupils at his Command took each the
hold of an Iron Handle, whereof there were Forty fixed round the Edges
of the Frame; and giving them a sudden Turn, the whole Disposition of
the Words was entirely changed. He then commanded Six and Thirty of the
Lads to read the several Lines softly as they appeared upon the Frame;
and where they found three or four Words together that might make Part
of a Sentence, they dictated to the four remaining Boys who were
Scribes. This work was repeated three or four Times, and at every Turn
the Engine was so contrived, that the Words shifted into new Places, as
the square Bits of Wood moved upside down.

Six hours a-day the young Students were employed in this Labour; and the
Professor showed me several Volumes in large Folio already collected, of
broken Sentences, which he intended to piece together, and out of those
rich Materials to give the World a compleat Body of Art and Sciences;
which however might be still improved, and much expedited, if the
Publick would raise a Fund for making and employing five Hundred such
Frames in _Lagado_....

Fortunately for Swift, who would have been horrified by it, he never
heard Russell Maloney’s classic story, “Inflexible Logic,” about six
monkeys pounding away at typewriters and re-creating the world great
literature. _Gulliver’s Travels_ is not listed in their accomplishments.

The French Revolution prompted no less an orator than Edmund Burke to
deliver in 1790 an address titled “Reflections on the French
Revolution,” in which he extols the virtues of the dying feudal order in
Europe. It galled Burke that “The Age of Chivalry is gone. That of
sophists, economists, and _calculators_ has succeeded, and the glory of
Europe is extinguished forever.”

Seventy years later another eminent Englishman named Darwin published a
book called _On the Origin of Species_ that in the eyes of many readers
did little to glorify man himself. Samuel Butler, better known for his
novel, _The Way of All Flesh_, wrote too of the mechanical being, and
was one of the first to point out just what sort of future Darwin was
suggesting. In the satirical _Erewhon_, he described the machines of
this mysterious land in some of the most prophetic writing that has been
done on the subject. It was almost a hundred years ago that Butler wrote
the first version, called “Darwin Among the Machines,” but the words
ring like those of a 1962 worrier over the electronic brain. Butler’s
character warns:

There is no security against the ultimate development of mechanical
consciousness in the fact of machines possessing little consciousness
now. Reflect upon the extraordinary advance which machines have made
during the last few hundred years, and note how slowly the animal and
vegetable kingdoms are advancing. The more highly organized machines are
creatures not so much of yesterday, as of the last five minutes, so to
speak, in comparison with past time.

Do not let me be misunderstood as living in fear of any actually
existing machine; there is probably no known machine which is more than
a prototype of future mechanical life. The present machines are to the
future as the early Saurians to man ... what I fear is the extraordinary
rapidity with which they are becoming something very different to what
they are at present.

Butler envisioned the day when the present rude cries with which
machines call out to one another will have been developed to a speech as
intricate as our own. After all, “... take man’s vaunted power of
calculation. Have we not engines which can do all manner of sums more
quickly and correctly than we can? What prizeman in Hypothetics at any
of our Colleges of Unreason can compare with some of these machines in
their own line?”

Noting another difference in man and his creation, Butler says,

... Our sum-engines never drop a figure, nor our looms a stitch; the
machine is brisk and active, when the man is weary, it is clear-headed
and collected, when the man is stupid and dull, it needs no slumber....
May not man himself become a sort of parasite upon the machines? An
affectionate machine-tickling aphid?

It can be answered that even though machines should hear never so well
and speak never so wisely, they will still always do the one or the
other for our advantage, not their own; that man will be the ruling
spirit and the machine the servant.... This is all very well. But the
servant glides by imperceptible approaches into the master, and we have
come to such a pass that, even now, man must suffer terribly on ceasing
to benefit the machines. If all machines were to be annihilated ... man
should be left as it were naked upon a desert island, we should become
extinct in six weeks.

Is it not plain that the machines are gaining ground upon us, when we
reflect on the increasing number of those who are bound down to them as
slaves, and of those who devote their whole souls to the advancement of
the mechanical kingdom?

Butler considers the argument that machines at least cannot copulate,
since they have no reproductive system. “If this be taken to mean that
they cannot marry, and that we are never likely to see a fertile union
between two vapor-engines with the young ones playing about the door of
the shed, however greatly we might desire to do so, I will readily grant
it. [But] surely if a machine is able to reproduce another machine
systematically, we may say that it has a reproductive system.”

Butler repeats his main theme. “... his [man’s] organization never
advanced with anything like the rapidity with which that of the machine
is advancing. This is the most alarming feature of the case, and I must
be pardoned for insisting on it so frequently.”

Then there is a startlingly clear vision of the machines “regarded as a
part of man’s own physical nature, being really nothing but
extra-corporeal limbs. Man ... as a machinate mammal.” This was feared
as leading to eventual weakness of man until we finally found “man
himself being nothing but soul and mechanism, an intelligent but
passionless principle of mechanical action.” And so the Erewhonians in
self-defense destroyed all inventions discovered in the preceding 271
years!


                       _Early Mechanical Devices_

During the nineteenth century, weaving was one of the most competitive
industries in Europe, and new inventions were often closely guarded
secrets. Just such an idea was that of Frenchman Joseph M. Jacquard, an
idea that automated the loom and would later become the basis for the
first modern computers. A big problem in weaving was how to control a
multiplicity of flying needles to create the desired pattern in the
material. There were ways of doing this, of course, but all of them were
unwieldy and costly. Then Jacquard hit on a clever scheme. If he took a
card and punched holes in it where he wanted the needles to be actuated,
it was simple to make the needles do his bidding. To change the pattern
took only another card, and cards were cheap. Patented in 1801, there
were soon thousands of Jacquard looms in operation, doing beautiful and
accurate designs at a reasonable price.

To show off the scope of his wonderful punched cards, Jacquard had one
of his looms weave a portrait of him in silk. The job took 20,000 cards,
but it was a beautiful and effective testimonial. And fatefully a copy
of the silk portrait would later find its way into the hands of a man
who would do much more with the oddly punched cards.

At about this same time, a Hungarian named Wolfgang von Kempelen decided
that machines could play games as well as work in factories. So von
Kempelen built himself a chess-playing machine called the Maelzel Chess
Automaton with which he toured Europe. The inventor and his machine
played a great game, but they didn’t play fair. Hidden in the innards of
the Maelzel Automaton was a second human player, but this disillusioning
truth was not known for some time. Thus von Kempelen doubtless spurred
other inventors to the task, and in a short while machines would
actually begin to play the royal game. For instance, a Spaniard named L.
Torres y Quevedo built a chess-playing machine in 1914. This device
played a fair “end game” using several pieces, and its inventor
predicted future work in this direction using more advanced machines.

Charles Babbage was an English scientist with a burning desire for
accuracy. When some mathematical tables prepared for the Astronomical
Society proved to be full of errors, he angrily determined to build a
machine that would do the job with no mistakes. Of course calculating
machines had been built before; but the machine Babbage had in mind was
different. In fact, he called it a “difference engine” because it was
based on the difference tables of the squares of numbers. The first of
the “giant computers,” it was to have hundreds of gears and shafts,
ratchets and counters. Any arithmetic problem could be set into it, and
when the proper cranks were turned, out would come an answer—the right
answer because the machine could not make a mistake. After doing some
preliminary work on his difference engine, Babbage interested the
government in his project since even though he was fairly well-to-do he
realized it would cost more money than he could afford to sink into the
project. Babbage was a respected scientist, Lucasian Professor of
Mathematics at Cambridge, and because of his reputation and the promise
of the machine, the Chancellor of the Exchequer promised to underwrite
the project.

For four years Babbage and his mechanics toiled. Instead of completing
his original idea, the scientist had succeeded only in designing a far
more complicated machine, one which would when finished weigh about two
tons. Because the parts he needed were advanced beyond the state of the
art of metalworking, Babbage was forced to design and build them
himself. In the process he decided that industry was being run all
wrong, and took time out to write a book. It was an excellent book, a
sort of forerunner to the modern science of operations research, and
Babbage’s machine shop was doing wonders for the metalworking art.

Undaunted by the lack of progress toward a concrete result, Babbage was
thinking bigger and bigger. He was going to scrap the difference engine,
or rather put it in a museum, and build a far better computer—an
“analytical engine.” If Jacquard’s punched cards could control the
needles on a loom, they could also operate the gears and other parts of
a calculating machine. This new engine would be one that could not only
add, subtract, multiply, and divide; it would be designed to control
itself. And as the answers started to come out, they would be fed back
to do more complex problems with no further work on the operator’s part.
“Having the machine eat its own tail!” Babbage called this sophisticated
bit of programming. This mechanical cannibalism was the root of the
“feedback” principle widely used in machines today. Echoing Watt’s steam
governor, it prophesied the coming control of machines by the machines
themselves. Besides this innovation, the machine would have a “store,”
or memory, of one thousand fifty-digit numbers that it could draw on,
and it would actually exercise judgment in selection of the proper
numbers. And as if that weren’t enough, it would print out the correct
answers automatically on specially engraved copper plates!

[Illustration:

  _Space Technology Laboratories_

  “As soon as an Analytical Engine exists, it will necessarily guide the
    future course of science. Whenever any result is sought by its aid,
    the question will then arise—by what course of calculation can these
    results be arrived at by the machine in the shortest time?” Charles
    Babbage—_The Life of a Philosopher_, 1861.
]

It was a wonderful dream; a dream that might have become an actuality in
Babbage’s own time if machine technology had been as advanced as his
ideas. But for Babbage it remained only a dream, a dream that never did
work successfully. The government spent £17,000, a huge sum for that day
and time, and bowed out. Babbage fumed and then put his own money into
the machine. His mechanics left him and became leaders in the
machine-tool field, having trained in Babbage’s workshops. In despair,
he gave up on the analytical engine and designed another difference
engine. An early model of this one would work to five accurate places,
but Babbage had his eyes on a much better goal—twenty-place accuracy. A
lesser man would have aimed more realistically and perhaps delivered
workable computers to the mathematicians and businessmen of the day.
There is a legend that his son did finish one of the simpler machines
and that it was used in actuarial accounting for many years. But Babbage
himself died in 1871 unaware of how much he had done for the computer
technology that would begin to flower a few short decades later.

Singlehandedly he had given the computer art the idea of programming and
of sequential control, a memory in addition to the arithmetic unit he
called a “mill,” and even an automatic readout such as is now standard
on modern computers. Truly, the modern computer was “Babbage’s dream
come true.”


                            _Symbolic Logic_

Concurrently with the great strides being made with mechanical computers
that could handle mathematics, much work was also being done with the
formalizing of the logic. As hinted vaguely in the syllogisms of the
early philosophers, thinking did seem amenable to being diagrammed, much
like grammar. Augustus De Morgan devised numerical logic systems, and
George Boole set up the logic system that has come to be known as
Boolean algebra in which reasoning becomes positive or negative terms
that can be manipulated algebraically to give valid answers.

John Venn put the idea of logic into pictures, and simple pictures at
that. His symbology looks for all the world like the three interlocking
rings of a well-known ale. These rings stand for the subject, midterm,
and predicate of the older Aristotelian syllogism. By shading the
various circles according to the major and minor premises, the user of
Venn circles can see the logical result by inspection. Implicit in the
scheme is the possibility of a mechanical or electrical analogy to this
visual method, and it was not long until mathematicians began at least
on the mechanical kind. Among these early logic mechanizers,
surprisingly, was Lewis Carroll who of course was mathematician Charles
L. Dodgson before he became a writer.

Carroll, who was a far busier man than most of us ever guess, marketed a
“Game of Logic,” with a board and colored cardboard counters that
handled problems like the following:

               All teetotalers like sugar.
               No nightingale drinks wine.

By arranging the counters on Carroll’s game board so that: All M are X,
and No Y is not-M, we learn that No Y is not-X! This tells the initiate
logician that no nightingale dislikes sugar; a handy piece of
information for bird-fancier and sugar-broker alike.

[Illustration:

  Lewis Carroll’s “Symbolic Logic.”
]

Charles, the third Earl Stanhope, was only slightly less controversial
than his prime minister, William Pitt. Scientifically he was far out
too, writing books on electrical theory, inventing steamboats,
microscopes, and printing presses among an odd variety of projects; he
also became interested in mechanical logic and designed the “Stanhope
Demonstrator,” a contrivance like a checkerboard with sliding panels. By
properly manipulating the demonstrator he could solve such problems as:

               Eight of ten children are bright.
               Four of these children are boys.

What are the minimum and maximum number of bright boys? A simple sliding
of scales on the Stanhope Demonstrator shows that two must be boys and
as many as four may be. This clever device could also work out
probability problems such as how many heads and tails will come up in so
many tosses of a coin.

In 1869 William S. Jevons, an English economist and expert logician,
built a logic machine. His was not the first, of course, but it had a
unique distinction in that it solved problems faster than the human
brain could! Using Boolean algebra principles, he built a “logical
abacus” and then even a “logical piano.” By simply pressing the keys of
this machine, the user could make the answer appear on its face. It is
of interest that Jevons thought his machine of no practical use, since
complex logical questions seldom arose in everyday life! Life, it seems,
was simpler in 1869 than it is today, and we should be grateful that
Jevons pursued his work through sheer scientific interest.

More sophisticated than the Jevons piano, the logic machine invented in
America by Allan Marquand could handle four terms and do problems like
the following:

       There are four schoolgirls, Anna, Bertha, Cora, and Dora.
       When Anna or Bertha, or both, remain home, Cora is at home.
       When Bertha is out, Anna is out.
       Whenever Cora is at home, Anna is too.
       What can we tell about Dora?

The machine is smart enough to tell us that when Dora is at home the
other three girls are all at home or out. The same thing is true when
Dora is out.


                           _The Census Taker_

Moving from the sophistication of such logic devices, we find a
tremendous advance in mechanical computers spurred by such a mundane
chore as the census. The 1880 United States census required seven years
for compiling; and that with only 50 million heads to reckon. It was
plain to see that shortly a ten-year census would be impossible of
completion unless something were done to cut the birth rate or speed the
counting. Dr. Herman Hollerith was the man who did something about it,
and as a result the 1890 census, with 62 million people counted, took
only one-third the time of the previous tally.

Hollerith, a statistician living in Buffalo, New York, may or may not
have heard the old saw about statistics being able to support
anything—including the statisticians, but there was a challenge in the
rapid growth of population that appealed to the inventor in him and he
set to work. He came up with a card punched with coded holes, a card
much like that used by Jacquard on his looms, and by Babbage on the
dream computer that became a nightmare. But Hollerith did not meet the
fate of his predecessors. Not stoned, or doomed to die a failure,
Hollerith built his card machines and contracted with the government to
do the census work. “It was a good paying business,” he said. It was
indeed, and his early census cards would some day be known generically
as “IBM cards.”

While Jacquard and Babbage of necessity used mechanical devices with
their punched cards, Hollerith added the magic of electricity to his
card machine, building in essence the first electrical computing
machine. The punched cards were floated across a pool of mercury, and
telescoping pins in the reading head dropped through the holes. As they
contacted the mercury, an electrical circuit was made and another
American counted. Hollerith did not stop with census work. Sagely he
felt there must be commercial applications for his machines and sold two
of the leading railroads on a punched-card accounting system. His firm
merged with others to become the Computing-Tabulating-Recording Company,
and finally International Business Machines. The term “Hollerith Coding”
is still familiar today.

[Illustration:

  _International Business Machines Corp._

  Hollerith tabulating machine of 1890, forerunner of modern computers.
]

Edison was illuminating the world and the same electrical power was
brightening the future of computing machines. As early as 1915 the Ford
Instrument Company was producing in quantity a device known as “Range
Keeper Mark I,” thought to be the first electrical-analog computer. In
1920, General Electric built a “short-circuit calculating board” that
was an analog or model of the real circuits being tested. Westinghouse
came up with an “alternating-current network analyzer” in 1933, and this
analog computer was found to be a powerful tool for mathematics.

[Illustration:

  _International Business Machines Corp._

  A vertical punched-card sorter used in 1908.
]

While scientists were putting the machines to work, writers continued to
prophesy doom when the mechanical man took over. Mary W. Shelley’s
_Frankenstein_ created a monster from a human body; a monster that in
time would take his master’s name and father a long horrid line of other
fictional monsters. Ambrose G. Bierce wrote of a diabolical
chess-playing machine that was human enough to throttle the man who beat
him at a game. But it remained for the Czech playwright Karel Čapek to
give the world the name that has stuck to the mechanical man. In Čapek’s
1921 play, _R.U.R._, for Rossum’s Universal Robots, we are introduced to
humanlike workers grown in vats of synthetic protoplasm. _Robota_ is a
Czech word meaning compulsory service, and apparently these mechanical
slaves did not take to servitude, turning on their masters and killing
them. Robot is generally accepted now to mean a mobile thinking machine
capable of action. Before the advent of the high-speed electronic
computer it had little likelihood of stepping out of the pages of a
novel or movie script.

As early as 1885, Allan Marquand had proposed an electrical logic
machine as an improvement over his simple mechanically operated model,
but it was 1936 before such a device was actually built. In that year
Benjamin Burack, a member of Chicago’s Roosevelt College psychology
department, built and demonstrated his “Electrical Logic Machine.” Able
to test all syllogisms, the Burack machine was unique in another
respect. It was the first of the portable electrical computers.

The compatibility of symbolic logic and electrical network theory was
becoming evident at about this time. The idea that yes-no corresponded
to on-off was beautifully simple, and in 1938 there appeared in one of
the learned journals what may fairly be called a historic paper.
Appearing in _Transactions of the American Institute of Electrical
Engineers_, “A Symbolic Analysis of Relay and Switching Circuits,” was
written by Claude Shannon and was based on his thesis for the M.S.
degree at the Massachusetts Institute of Technology a year earlier. One
of its important implications was that the programming of a computer was
more a logical than an arithmetical operation. Shannon had laid the
groundwork for logical computer design; his work made it possible to
teach the machine not only to add but also to think. Another monumental
piece of work by Shannon was that on information theory, which
revolutionized the science of communications. The author is now on the
staff of the electronics research laboratory at M.I.T.

Two enterprising Harvard undergraduates put Shannon’s ideas to work on
their problems in the symbolic logic class they were taking. Called a
Kalin-Burkhart machine for its builders, this electrical logic machine
did indeed work, solving the students’ homework assignments and saving
them much tedious paperwork. Interestingly, when certain logical
questions were posed for the machine, its circuits went into
oscillation, making “a hell of a racket” in its frustration. The
builders called this an example of “Russell’s paradox.” A typical
logical paradox is that of the barber who shaved all men who didn’t
shave themselves—who shaves the barber? Or of the condemned man
permitted to make a last statement. If the statement is true, he will be
beheaded; if false, he will hang. The man says, “I shall be hanged,” and
thus confounds his executioners as well as logic, since if he is hanged,
the statement is indeed true, and he should have been beheaded. If he is
beheaded, the statement is false, and he should have been hanged
instead.

World War II, with its pressingly complex technological problems,
spurred computer work mightily. Men like Vannevar Bush, then at Harvard,
produced analog computers called “differential analyzers” which were
useful in solving mathematics involved in design of aircraft and in
ballistics problems.

A computer built by General Electric for the gunsights on the World War
II B-29 bomber is typical of applications of analog devices for
computing and predicting, and is also an example of early airborne use
of computing devices. Most computers, however, were sizable affairs. One
early General Electric analog machine, described as a hundred feet long,
indicates the trend toward the “giant brain” concept.

Even with the sophistication attained, these computers were hardly more
than extensions of mechanical forerunners. In other words, gears and
cams properly proportioned and actuated gave the proper answers whether
they were turned by a manual crank or an electrical motor. The digital
computer, which had somehow been lost in the shuffle of interest in
computers, was now appearing on the scientific horizon, however, and in
this machine would flower all the gains in computers from the abacus to
electrical logic machines.


                         _The Modern Computer_

Many men worked on the digital concept. Aiken, who built the
electromechanical Mark I at Harvard, and Williams in England are
representative. But two scientists at the University of Pennsylvania get
the credit for the world’s first electronic digital computer, ENIAC, a
30-ton, 150-kilowatt machine using vacuum tubes and semiconductor diodes
and handling discrete numbers instead of continuous values as in the
analog machine. The modern computer dates from ENIAC, Electronic
Numerical Integrator And Computer.

[Illustration:

  _Remington Rand UNIVAC_

  ENIAC in operation. This was the first electronic digital computer.
]

Shannon’s work and the thinking of others in the field indicated the
power of the digital, yes-no, approach. A single switch can only be on
or off, but many such switches properly interconnected can do amazing
things. At first these switches were electromechanical; in the
Eckert-Mauchly ENIAC, completed for the government in 1946, vacuum tubes
in the Eccles-Jordan “flip-flop” circuit married electronics and the
computer. The progeny have been many, and their generations faster than
those of man. ENIAC has been followed by BINAC and MANIAC, and even
JOHNNIAC. UNIVAC and RECOMP and STRETCH and LARC and a whole host of
other machines have been produced. At the start of 1962 there were some
6,000 electronic digital computers in service; by year’s end there will
be 8,000. The golden age of the computer may be here, but as we have
seen, it did not come overnight. The revolution has been slow, gathering
early momentum with the golden wheels of Homer’s mechanical
information-seeking vehicles that brought the word from the gods. Where
it goes from here depends on us, and maybe on the computer itself.


------------------------------------------------------------------------


    “_Theory is the guide to practice, and practice is the ratification
       and life of theory._”

                    —John Weiss




                         3: How Computers Work


In the past decade or so, an amazing and confusing number of computing
machines have developed. To those of us unfamiliar with the beast, many
of them do not look at all like what we imagined computers to be; others
are even more awesome than the wildest science-fiction writer could
dream up. On the more complex, lights flash, tape reels spin dizzily,
and printers clatter at mile-a-minute speeds. We are aware, or perhaps
just take on faith, that the electronic marvel is doing its sums at so
many thousand or million per second, cranking out mathematical proofs
and processing data at a rate to make mere man seem like the dullest
slowpoke. Just how computers do this is pretty much of a mystery unless
we are of the breed that works with them. Actually, in spite of all the
blurring speed and seeming magic, the basic steps of computer operation
are quite simple and generally the same for all types of machines from
the modestly priced electromechanical do-it-yourself model to STRETCH,
MUSE, and other ten-million-dollar computers.

It might be well before we go farther to learn a few words in the
lexicon of the computer, words that are becoming more and more a part of
our everyday language. The following glossary is of course neither
complete nor technical but it will be helpful in following through the
mechanics of computer operation.


                          COMPUTER DICTIONARY

ACCESS TIME—Time required for computer to locate data and transfer it
from one computer element to another.

ADDER—Device for forming sums in the computer.

ADDRESS—Specific location of information in computer memory.

ANALOG COMPUTER—A physical or electrical simulator which produces an
analogy of the mathematical problem to be solved.

ARITHMETIC UNIT—Unit that performs arithmetical and logical operations.

BINARY CODE—Representation of numbers or other information using only
one and zero, to take advantage of open and closed circuits.

BIT—A binary digit, either one or zero; used to make binary numbers.

BLOCK—Group of words handled as a unit, particularly with reference to
input and output.

BUFFER—Storage device to compensate for difference in input and
operation rate.

CONTROL UNIT—Portion of the computer that controls arithmetic and
logical operations and transfer of information.

DELAY LINE—Memory device to store and later reinsert information; uses
physical, mechanical, or electrical techniques.

DIGITAL COMPUTER—A computer that uses discrete numbers to represent
information.

FLIP-FLOP—A circuit or device which remains in either of two states
until the application of a signal.

GATE—A circuit with more than one input, and an output dependent on
these inputs. An AND gate’s output is energized only when all inputs are
energized. An OR gate’s output is energized when one or more inputs are
energized. There are also NOT-AND gates, EXCLUSIVE-OR gates, etc.

LOGICAL OPERATION—A nonarithmetical operation, i.e., decision-making,
data-sorting, searching, etc.

MAGNETIC DRUM—Rotating cylinder storage device for memory unit; stores
data in coded form.

MATRIX—Circuitry for transformation of digital codes from one type to
another; uses wires, diodes, relays, etc.

MEMORY UNIT—That part of the computer that stores information in machine
language, using electrical or magnetic techniques.

MICROSECOND—One millionth of a second.

MILLISECOND—One thousandth of a second.

NANOSECOND—One billionth of a second.

PARALLEL OPERATION—Digital computer operation in which all digits are
handled simultaneously.

PROGRAMMING—Steps to be executed by computer to solve problem.

RANDOM ACCESS—A memory system that permits more nearly equal access time
to all memory locations than does a nonrandom system. Magnetic core
memory is a random type, compared with a tape reel memory.

REAL TIME—Computer operation simultaneous with input of information;
e.g., control of a guided missile or of an assembly line.

REGISTER—Storage device for small amount of information while, or until,
it is needed.

SERIAL OPERATION—Digital computer operation in which all digits are
handled serially.

STORAGE—Use of drums, tapes, cards, and so on to store data outside the
computer proper.


                         _The Computer’s Parts_

Looking at computers from a distance, we are vaguely aware that they are
given problems in the form of coded instructions and that through some
electronic metamorphosis this problem turns into an answer that is
produced at the readout end of the machine. There is an engineering
technique called the “black box” concept, in which we are concerned only
with input to this box and its output. We could extend this concept to
“black-magic box” and apply it to the computer, but breaking the system
down into its components is quite simple and much more informative.

There are five components that make up a computer: input, control,
arithmetic (or logic) unit, memory, and output. As machine intelligence
expert, Dr. W. Ross Ashby, points out, we can get no more out of a
brain—mechanical or human—than we put into it. So we must have an input.
The kind of input depends largely on the degree of sophistication of the
machine we are considering.

With the abacus we set in the problem mechanically, with our fingers.
Using a desk calculator we punch buttons: a more refined mechanical
input. Punched cards or perforated tapes are much used input methods. As
computers evolve rapidly, some of them can “read” for themselves and the
input is visual. There are also computers that understand verbal
commands.

Input should not be confused with the control portion of the computer’s
anatomy. We feed in data, but we must also tell the computer what to do
with the information. Shall it count the number of cards that fly
through it, or shall it add the numbers shown on the cards, record the
maximum and minimum, and print out an average? Control involves
programming, a computer term that was among the first to be assimilated
into ordinary language.

The arithmetic unit—that part of the computer that the pioneer Babbage
called his “mill”—is the nuts and bolts end of the business. Here are
the gears and shafts, the electromechanical relays, or the vacuum tubes,
transistors, and magnetic cores that do the addition, multiplication,
and other mathematical operations. Sometimes this is called the “logic”
unit, since often it manipulates the ANDS, ORS, NORS, and other
conjunctives in the logical algebra of Boole and his followers.

The memory unit is just that; a place where numbers, words, or other
data are stored and ready to be called into use whenever needed. There
are two broad types of memory, internal and external, and they parallel
the kind of memory we use ourselves. While our brain can store many,
many facts, it does have a practical limit. This is why we have phone
books, logarithm tables, strings around fingers, and so on. The computer
likewise has its external memory that may store thousands of times the
capacity of its internal memory. Babbage’s machine could remember a
thousand fifty-digit numbers; today’s large computers call on millions
of bits of data.

[Illustration:

  Conversion of problem to machine program.
]

After we have dumped in the data and told the computer what to do with
them, and the arithmetic and memory have collaborated, it remains only
for the computer to display the result. This is the output of the
computer, and it can take many forms. If we are using a simple analog
computer such as a slide rule, the answer is found under the hairline on
the slide. An electronic computer in a bank prints out the results of
the day’s transactions in neat type at hundreds of lines a minute. The
SAGE defense computer system displays an invading bomber and plots the
correct course for interceptors on a scope; a computer in a playful mood
might type out its next move—King to Q7 and checkmate.

With this sketchy over-all description to get us started, let us study
each unit in a little more detail. It is interesting to compare these
operations with those of our human computer, our brain, as we go along.

[Illustration:

  _Remington Rand UNIVAC_

  A large computer, showing the different parts required.
]


                                _Input_

An early and still very popular method of getting data into the computer
is the punched card. Jacquard’s clever way of weaving a pattern got into
the computer business through Hollerith’s census counting machines.
Today the ubiquitous IBM card can do these tasks of nose counting and
weaving, and just about everything else in between. Jacquard used the
punched holes to permit certain pins to slide through. Hollerith
substituted the mercury electrical contact for the loom’s flying
needles. Today there are many other ways of “reading” the cards. Metal
base plate and springs, star wheels, even photoelectric cells are used
to detect the presence or absence of the coded holes. A human who knows
the code can visually extract the information; a blind man could do it
by the touch system. So with the computer, there are many ways of
transferring data.

[Illustration:

  _Remington Rand_ UNIVAC

  The Computer’s Basic Parts.
]

An obvious requirement of the punched card is that someone has to punch
the holes in the first place. This is done with manually operated
punches, power punches, and even automatic machines that handle more
than a hundred cards a minute. Punched cards, which fall into the
category called computer “software,” are cheap, flexible, and compatible
with many types of equipment.

Particularly with mathematical computations and scientific research,
another type of input has become popular, that of paper tape. This in
effect strings many cards together and puts them on an easily handled
roll. Thus a long series of data can be punched without changing cards,
and is conveniently stored for repeated use. Remember the old
player-piano rolls of music? These actually formed the input for one
kind of computer, a musical machine that converted coded holes to
musical sounds by means of pneumatic techniques. Later in this chapter
we will discuss some modern pneumatic computers.

More efficient than paper is magnetic tape, the same kind we use in our
home recording instruments. Anyone familiar with a tape recorder knows
how easy it is to edit or change something on a tape reel. This is a big
advantage over punched cards or paper tapes which are physically altered
by the data stored on them and cannot be corrected. Besides this,
magnetic tape can hold many more “bits” of information than paper and
also lends itself to very rapid movement through the reading head of the
computer. For example, standard computer tape holds seven tracks, each
with hundreds of bits of information per inch. Since there are thousands
of feet on a ten-inch reel, it is theoretically possible to pack 40
_million_ bits on this handful of tape!

Since the computer usually can operate at a much higher rate of speed
than we can put information onto tape, it is often the practice to have
a “buffer” in the input section. This receiving station collects and
stores information until it is full, then feeds it to the computer which
gobbles it up with lightning speed. Keeping a fast computer continuously
busy may require many different inputs.

Never satisfied, computer designers pondered the problem of all the lost
time entailed in laboriously preparing cards or tapes for the ravenous
electronic machine. The results of this brain-searching are interesting,
and they are evident in computers that actually read man-talk. Computers
used in the post office and elsewhere can optically read addresses as
well as stamps; banks have computers that electrically read the coded
magnetic ink numbers on our checks and process thousands of times as
many as human workers once did. This optical reading input is not
without its problems, of course. Many computers require a special type
face to be used, and the post office found that its stamp recognizer was
mistaking Christmas seals for foreign stamps. Improved read heads now
can read hand-printed material and will one day master our widely
differing human scrawls. This is of course a boon to the “programmer” of
lengthy equations who now has to translate the whole problem into
machine talk before the machine can accept it.

If a machine can read, why can’t it understand verbal input as well?
Lazy computer engineers have pushed this idea, and the simplest input
system of all is well on the way to success. Computers today can
recognize numbers and a few words, and the Japanese have a typewriter
that prints out the words spoken to it! These linguistic advances that
electronic computers are making are great for everyone, except perhaps
the glamorized programmer, a new breed of mathematical logician whose
services have been demanded in the last few years.

[Illustration:

  Magnetic Tape - Paper Tape - IBM Card - Magnetic Ink Characters
]


                               _Control_

Before we feed the problem into the machine, or before we give it some
“raw” data to process, we had better tell our computer what we want it
to do. All the fantastic speed of our electrons will result in a
meaningless merry-go-round, or perhaps a glorious machine-stalling short
circuit unless the proper switches open and close at the right time.
This is the job of the control unit of the computer, a unit that
understands commands like “start,” “add,” “subtract,” “find the square
root,” “file in Bin B,” “stop,” and so on. The key to all the computer’s
parts working together in electronic harmony is its “clock.” This
timekeeper in effect snaps its fingers in perfect cadence, and the
switches jump at its bidding. Since the finger-snapping takes place at
rates of millions of snaps a second, the programmer must be sure he has
instructed the computer properly.

The ideal programmer is a rare type with a peculiarly keen brain that
sometimes takes seemingly illogical steps to be logical. Programmers are
likely to be men—or women, for there is no sex barrier in this new
profession—who revel in symbolic logic and heuristic or “hunch”
reasoning. Without a program, the computer is an impressively elaborate
and frighteningly expensive contraption which cannot tell one number
from another. The day may come when the mathematician can say to the
machine, “Prove Fermat’s last theorem for me, please,” or the engineer
simply wish aloud for a ceramic material that melts at 15,000° C. and
weighs slightly less than Styrofoam. Even then the human programmer will
not start drawing unemployment insurance, of course. If he is not
receiving his Social Security pension by then he will simply shift to
more creative work such as thinking up more problems for the machine to
solve.

Just as there are many jobs for the computer, so there are many kinds of
programs. On a very simple, special-purpose computer, the program may be
“wired-in,” or fixed, so that the computer can do that particular job
and no other. On a more flexible machine, the program may still be quite
simple, perhaps no more than a card entered in a desk unit by an airline
ticket agent to let the computer arrange a reservation for three tourist
seats on American Airlines jet flight from Phoenix to Chicago at 8:20
A.M. four days from now. On a general-purpose machine, capable of many
problems, the program may be unique, a one-of-a-kind highly complex set
of instructions that will make the computer tax its huge memory and do
all sorts of mental “nip-ups” before it reaches a solution.

A computer that understands about sixty commands has been compared to a
Siamese elephant used for teak logging; the animal has about that many
words in its vocabulary. Vocabulary is an indication of computer as well
as human sophistication. The trend is constantly toward
less-than-elephant size, and more-than-elephant vocabulary.

The programmer’s work can be divided into four basic phases: _analysis_
of the problem; _application_ or matching problem requirements with the
capabilities of the right computer; _flow charting_ the various
operations using symbolic diagrams; and finally, _coding_ or translating
the flow chart into language the computer knows.

The flow chart to some extent parallels the way our own brains solve
logic problems, or at least the way they _ought_ to solve them. For
example, a computer might be instructed to select the smallest of three
keys. It would compare A and B, discard the larger, and then compare
with C, finally selecting the proper one. This is of course such a
ridiculously simple problem that few of us would bother to use the
computer since it would take much longer to plot the flow chart than to
select the key by simple visual inspection. But the logical principle is
the same, even when the computer is to be told to analyze all the
business transactions conducted by a large corporation during the year
and advise a program for the next year which will show the most profit.
From the symbolic flow chart, the programmer makes an operational flow
chart, a detailed block diagram, and finally the program itself.
Suitably coded in computer language, this program is ready for the
computer’s control unit.

With a problem of complex nature, such as one involving the firing of a
space vehicle, programmers soon learned they were spending hours, or
even days, on a problem which the computer proceeded to zip through in
minutes or seconds. It was something like working all year building an
elaborate Fourth of July fireworks display, touching the match, and
seeing the whole thing go up in spectacular smoke for a brief moment. Of
course the end justifies the means in either case, and as soon as the
computer has quit whirring, or the skyrockets faded out, the programmer
gets back to work. But some short cuts were learned.

Even a program for a unique problem is likely to contain many
“subroutines” just like those in other problems. These are used and
re-used; some computers now have libraries of programs they can draw on
much as we call on things learned last week or last year.

With his work completed, the programmer’s only worry is that an error
might exist in it, an error that could raise havoc if not discovered.
One false bit of logic in a business problem; a slight mathematical
boner in a design for a manned missile, could be catastrophic since our
technology is so complicated that the mistake might be learned only when
disaster struck. So the programmer checks and rechecks his work until he
is positive _he_ has not erred.

How about the computer? It checks itself too; so thoroughly that there
is no danger of it making a mistake. Computer designers have been very
clever in this respect. One advanced technique is “majority rule”
checking. Not long ago when the abacus was used even in banking, the
Japanese were aware that a single accountant might make a false move and
botch up the day’s tally. But if two operators worked the same problem
and got the same answer, the laws of probability rule that the answer
can be accepted. If the sums do not agree, though, which man is right?
To check further, and save the time needed to go through the whole
problem again, _three_ abacuses, or abaci, are put through their paces.
Now if two answers agree, chances are they are the right solution. If
all three are different, the bank had better hire new clerks!

[Illustration:

  _Remington Rand UNIVAC_

  A word picture “flow chart” of the logical operation of selecting the
    proper key.
]


                         _Arithmetic or Logic_

Now that our computer has the two necessary ingredients of input and
control, the arithmetic or logic unit can get busy. Babbage called this
the “mill,” and with all the whirring gears and clanking arms his engine
boasted, the term must have been accurate. Today’s computer is much
quieter since in electronic switches the only moving parts are the
electrons themselves and these don’t make much of a racket. Such
switches have another big advantage in that they open and close at a
great rate, practically the speed of light. The fastest computers use
switches that act in _nanoseconds_, or billionths of a second. In one
nanosecond light itself travels only a foot.

The computer may be likened to someone counting on two of his fingers.
Instead of the decimal or ten-base system, most computers use binary
arithmetic, which has a base of two. But fingers that can be counted in
billionth parts of a second can handle figures pretty fast, and the
computer has learned some clever tricks that further speed things up. It
can only add, but by adroit juggling it subtracts by using the
complement of the desired number, a technique known to those familiar
with an ordinary adding machine. There are also some tricks to
multiplying that allow the computer again to simply add and come up with
the answer.

With pencil and paper we can multiply 117 times 835 easily. Remember,
though, that the computer can only add, and that it was once called a
speedy imbecile. The most imbecilic computer might solve the problem by
adding 117 to itself 835 times. A smarter model will reverse the
procedure and handle only 117 numbers. The moron type of computer is a
bit more clever and sets up the problem this way:

                           835
                           835
                           835
                           835
                           835
                           835
                           835
                          8350
                         83500
                         ——
                         97695

A moment’s reflection will show that this is the same as adding 7 times
835, 10 times 835, and 100 times 835. And of course the computer arrives
at the answer in about the time it takes us to start drawing the line
under our multiplier.

[Illustration:

  _The Bendix Corp., Computer Division_

  Assembly of printed-circuit component “packages” into computer.
]

Perhaps smarting under the unkind remarks about its mental ability, the
computer has lately been trying some new approaches to the handling of
complex arithmetical problems. Instead of adding long strings of
numbers, it will take a guess at the result, do some smart checking,
adjust its figures, and shortly arrive at the right solution. For
nonarithmetical problems, the computer substitutes yes and no for 1 and
0 and blithely solves problems in logic at the same high rate of speed.


                                _Memory_

When we demonstrated our superiority earlier in multiplying instead of
adding the numbers in the problem, we were drawing on our memory:
recalling multiplication tables committed to memory when we were quite
young. Babbage’s “store” in his difference engine, you will recall,
could memorize a thousand fifty-digit numbers, a feat that would tax
most of us. The grandchildren of the Babbage machine can call on as many
as a billion bits of information stored on tape. As you watch the reels
of tape spinning, halting abruptly, and spinning again so purposefully,
remember that the computer is remembering. In addition to its large
memory, incidentally, a computer may also have a smaller “scratch-pad”
memory to save time.

Early machines used electromechanical relays or perhaps vacuum-tube
“flip-flops” for memory. Punched-card files store data too. To speed up
the access to information, designers tried the delay-line circuit, a
device that kept information circulating in a mercury or other type of
delay. Magnetic drums and discs are also used. Magnetic tape on reels is
used more than any other memory system for many practical reasons. There
is one serious handicap with the tape system, however. Information on
it, as on the drum, disc, file card, or delay line, is serial, that is,
it is arranged in sequence. To reach a certain needed bit of data might
require running through an entire reel of tape. Even though the tape
moves at very high speed, time is lost while the computer’s arithmetic
unit waits. For this reason the designers of the most advanced computers
have gone to “random access” instead of sequential memory for part of
the machine.

Tiny cores of ferrite material which has the desired magnetic properties
are threaded on wires. These become memory elements, as many as a
hundred of them in an area the size of a postage stamp. Each core is at
the intersection of two wires, one horizontal and one vertical. Each
core thus has a unique “address” and because of the arrangement of the
core matrix, any address can be reached in about the same amount of time
as any other. Thus, instead of spinning the tape several hundred feet to
reach address number 6,564, the computer simply closes the circuit of
vertical row 65 and horizontal row 64, and there is the desired bit of
information in the form of a magnetic field in the selected core.

Hot on the heels of the development of random-access core memories came
that of thin metallic film devices and so-called cryogenic or supercold
magnetic components that do the same job as the ferrite cores but take
only a fraction of the space. Some of these advanced devices also lend
themselves to volume production and thus pave the way for memories with
more and more information-storage capability.

[Illustration:

  _International Business Machines Corp._

  Magnetic core plane, the computer’s memory.
]

In the realm of “blue-sky” devices, sometimes known as “journalistors,”
are molecular block memories. These chunks of material will contain
millions of bits of information in cubic inches of volume, and some way
of three-dimensional scanning of the entire block will be developed.
With such a high-volume memory, the computer of tomorrow will fit on a
desk top instead of requiring rows and rows of tape-filled machines.

Today, tape offers the cheapest “per bit” storage, and it is necessary
to use the external or peripheral type of information storage. This is
not much of a problem except for the matter of space. Since most
computers are electronic, all that is required to tie the memory units
to the arithmetic unit is wire connections. Douglas Aircraft ties
computers in its California and North Carolina plants with 2,400 miles
of telephone hookup. Sometimes even wires are not necessary. In the Los
Angeles area, North American Aviation has a number of plants separated
by as many as forty miles. Each plant is quite capable of using the
computers in the other locations, with a stream of digits beamed by
microwave radio from one to the other. Information can be transferred in
this manner at rates up to 65,000 bits per second.


                                _Output_

Once the computer has taken the input of information, been instructed
what to do, and used its arithmetic and memory, it has done the bulk of
the work on the problem. But it must now reverse the procedure that took
place when information flowed into it and was translated into electrical
impulses and magnetic currents. It could convey the answer to another
machine that spoke its language, but man would find such information
unintelligible. So the computer has an output section that translates
back into earth language.

Babbage’s computer was to have printed out its answers on metal plates,
and many computers today furnish punched cards or tape as an output.
Others print the answers on sheets of paper, so rapidly that a page of
this book would take little more than a second to produce! One of the
greatest challenges of recent years is that of producing printing
devices fast enough to exploit fully the terrific speeds of electronic
computing machines. There would be little advantage in a computer that
could add all the digits in all the phone books in the world in less
than a minute if it took three weeks to print out the answer.

Impact printers, those that actually strike keys against paper, have
been improved to the point where they print more than a thousand lines
of type, each with 120 characters in it, per minute. But even this is
not rapid enough in some instances, and completely new kinds of printers
have been developed. One is the Charactron tube, a device combining a
cathode-ray tube, something like the TV picture tube, with an interposed
64-character matrix about half an inch in diameter. Electrical impulses
deflect the electron beam in the tube so that it passes through the
proper matrix character and forms that image on the face of the tube.
This image then is printed electrostatically on the treated paper rather
than with a metal type face. With no moving parts except the paper, and
of course the electrons themselves, the Charactron printer operates
close to the speed of the computer itself, and produces 100,000 words a
minute. This entire book could be printed out in about forty-five
seconds in this manner.

[Illustration:

  _Minneapolis-Honeywell,
  Electronic Data Processing Division_

  A high-speed printer is the output of this computer. It prints 900
    _lines_ a minute.
]

There are many other kinds of outputs. Some are in the form of payroll
checks, rushing from the printer at the rate of 10,000 an hour. Some are
simply illuminated numbers and letters on the face of the computer. As
mentioned earlier, the SAGE air defense computer displays the tracks of
aircraft and missiles on large screens, each accurately tagged for
speed, altitude, and classification. The computer may even speak its
answer to us audibly.

General Electric engineers have programmed computers to play music, and
come up with a clever giveaway record titled “Christmas Carols in 210
Time,” à la pipe-organ solo. Some more serious musical work is now being
done in taking a musical input fed to a computer, programming it for
special effects including the reverberant effect of a concert hall, and
having that played as the output.

A more direct vocal output is the spoken word. Some computers have this
capability now, with a modest vocabulary of their own and an extensive
tape library to draw from. As an example, Gilfillan Radio has produced a
computerized ground-control-approach system that studies the radar
return of the aircraft being guided, and “tells” the pilot how to fly
the landing. All the human operator does is monitor the show.

The system uses the relatively simple method of selecting the correct
words from a previously tape-recorded human voice. More sophisticated
systems will be capable of translating code from the computer directly
into an audible output. One very obvious advantage of such an automatic
landing system is that the computer is never subject to a bad day,
nerves, or fright. It will talk the aircraft down calmly and
dispassionately, albeit somewhat mechanically.

These then are the five basic parts of a computer or computer system:
input, control, arithmetic-logic, memory, and output. Remember that this
applies equally to simple and complex machines, and also to computers
other than the more generally encountered electronic types. For while
the electronic computer is regarded as the most advanced, it is not
necessarily the final result of computer development. Let us consider
some of the deviants, throwbacks, and mutations of the computer species.

[Illustration:

  _Kearfott Division, General Precision, Inc._

  The tiny black box is capable of the same functions as the larger
    plastic laboratory model pneumatic digital computer.

  Packaging densities of more than 2,000 elements per cubic inch are
    expected.
]


                       _Another Kind of Computer_

We have discussed mechanical, electromechanical, electrical, and
electronic computers. There are also those which make use of quite
different media for their operation: hydraulics, air pressure, and even
hot gases. The pneumatic is simplest to explain, and also has its
precedent in the old player-piano mentioned earlier.

Just as an electric or electronic switch can be open or closed, so can a
pneumatic valve. The analogy carries much further. Some of the basic
electronic components used in computers are diodes, capacitors,
inductors, and “flip-flop” circuits which we have talked of. Each of
these, it turns out, can be approximated by pneumatic devices.

The pneumatic diode is the simplest component, being merely an orifice
or opening through which gas is flowing at or above the speed of sound.
Under these conditions, any disturbance in pressure “upstream” of the
orifice will move “downstream” through the orifice, but any such
happening downstream cannot move upstream. This is analogous to the way
an electronic diode works in the computer, a one-way valve effect.

The electrical capacitor with its stored voltage charge plays an
important part in computer circuitry. A plenum chamber, or box holding a
volume of air, serves as a pneumatic capacitor. Similarly, the effect of
an inductor, or coil, is achieved with a long pipe filled with moving
air.

The only complicated element in our pneumatic computer building blocks
is the flip-flop, or bistable element. A system of tubes, orifices, and
balls makes a device that assumes one position upon the application of
pneumatic force, and the other upon a successive application, similar to
the electronic flip-flop. Pneumatic engineers use terms like “pressure
drop” and “pneumatic buffering,” comparable to voltage drop and
electrical buffering.

A good question at this point is just why computer designers are even
considering pneumatic methods when electronic computers are doing such a
fine job. There are several reasons that prompt groups like the Kearfott
Division of General Precision Inc., AiResearch, IBM’s Swiss Laboratory,
and the Army’s Diamond Ordnance Fuze Laboratory to develop the
air-powered computers. One of these is radiation susceptibility. Diodes
and transistors have an Achilles heel in that they cannot take much
radiation. Thus in military applications, and in space work, electronic
computers may be incapable of proper operation under exposure to fallout
or cosmic rays. A pneumatic computer does not have this handicap.

High temperature is another bugaboo of the electronic computer. For
operation above 100° C., for instance, it is necessary to use expensive
silicon semiconductor elements. The cryogenic devices we talked of
require extremely low temperatures and are thus also ruled out in hot
environments. The pneumatic computer, on the other hand, can actually
operate on the exhaust gases of a rocket with temperatures up to 2000°
F. There may be something humanlike in this ability to operate on hot
air, but there are more practical reasons like simplicity, light weight,
and low cost.

The pneumatic computer, of course, has limitations of its own. The most
serious is that of speed, and its top limit seems to be about 100
kilocycles a second. Although this sounds fast—a kilocycle being a
thousand cycles, remember—it is tortoise-slow compared with the
50-megacycle speed of present electronic machines. But within its
limitations the pneumatic machine can do an excellent job. Kearfott
plans shrinking 3,000 pneumatic flip-flops and their power supply and
all circuitry into a one-inch cube; and packing a medium-size
general-purpose digital computer complete with memory into a case 5-1/2
inches square and an inch thick. Such a squeezing of components surely
indicates _compressed_ air as a logical power supply!

Going beyond the use of air as a medium, Army researchers have worked
with “fluid” flip-flops capable of functioning at temperatures ranging
from minus 100° to plus 7,000° F.! The limit is dictated only by the
material used to contain the fluid, and would surely meet requirements
for the most rigorous environment foreseeable.

The fluid flip-flop operates on a different principle from its pneumatic
cousin, drawing on fluid dynamics to shift from one state to the other.
Fluid dynamics permits the building of switches and amplifiers that
simulate electronic counterparts adequately, and the Army’s Diamond
Ordnance Fuze Laboratory has built such oscillators, shift registers,
and full adders, the flesh and bones of the computer. Researchers
believe components can be built cheaply and that ultimately a complete
fluid computer can be assembled.

The X-15 is cited as an example of a good application for fluid-type
computing devices. The hypersonic aircraft flies so fast it glows, and a
big part of its problem is the cooling of a large amount of electronic
equipment that generates additional heat to compound the difficulty.
Missiles and space vehicles have similar requirements.

Tomorrow’s computer may use liquid helium or a white-hot plasma jet
instead of electronics or gas as a medium. It may use a medium nobody
has dreamed of yet, or one tried earlier and discarded. Regardless of
what it uses, it will probably work on the same basic theory and
principles we’ve outlined here. And try as we may, we will get no more
out of it than we put in.

[Illustration:

  By Herbert Goldberg © 1961 Saturday Review

  “Is this your trouble?”
]


------------------------------------------------------------------------


    “_It is the machines that make life complicated, at the
    same time that they impose on it a high tempo._”

                    —Carl Lotus Becker




                       4: Computer Cousins—Analog
                                and Digital


There are many thousands of computers in operation today—in enough
different outward varieties to present a hopeless classification task to
the confused onlooker. Actually there are only two basic types of
computing machines, the analog and the digital. There is also a third
computer, an analog-digital hybrid that makes use of the better features
of each to do certain jobs more effectively.

The distinction between basic types is clear-cut and may be explained in
very simple terms. Again we go to the dictionary for a starting point.
Webster says: “Analogue.—That which is analogous to some other thing.”
Even without the terminal _ue_, the analog computer is based on the
principle of analogy. It is actually a model of the problem we wish to
solve. A tape measure is an analog device; so is a slide rule or the
speedometer in your car. These of course are very simple analogs, but
the principle of the more complex ones is the same. The analog computer,
then, simulates a physical problem and deals in quantities which it can
measure.

Some writers feel that the analog machine is not a computer at all in
the strict sense of the word, but actually a laboratory model of a
physical system which may be studied and measured to learn certain
implicit facts.

[Illustration:

  _Minneapolis-Honeywell Computer Center_

  A multimillion dollar aerospace computer facility. On left is an array
    of 16 analog computers; at right is a large digital data-processing
    system.

  The facility can perform scientific and business tasks simultaneously.
]

The dictionary also gives us a good clue to the digital computer:
“Digital.—Of the fingers or digits.” A digital machine deals in digits,
or discrete units, in its calculations. For instance, if we ask it to
multiply 2 times 2, it answers that the product is exactly 4. A slide
rule, which we have said is an analog device, might yield an answer of
3.98 or 4.02, depending on the quality of its workmanship and our
eyesight.

The term “discrete” describes the units used by the digital machine; an
analog machine deals with “continuous” quantities. When you watch the
pointer on your speedometer you see that it moves continuously from zero
to as fast as you can or dare drive. The gas gauge is a graphic
presentation of the amount of fuel in the tank, just as the speedometer
is a picture of your car’s speed. For convenience we interpolate the
numbers 10, 20, 30, 1/4, 1/2, and so on. What we do, then, is to convert
from a continuous analog presentation to a digital answer with our eyes
and brain. This analog-to-digital conversion is not without
complications leading to speeding tickets and the inconvenience of
running out of gas far from a source of supply.

A little thought will reveal that even prior to computers there were two
distinct types of calculating; those of measuring (analog) and of
counting (digital). Unless we are statisticians, we encounter 2-1/2 men
or 3-1/2 women about as frequently as we are positive that there is
exactly 10 gallons of fuel in the gas tank. In fact, we generally use
the singular verb with such a figure since the 10 gallons is actually an
arbitrary measurement we have superimposed on a quantity of liquid.
Counting and measuring, then, are different things.

Because of the basic differences in the analog and digital computers,
each has its relative advantages and disadvantages with respect to
certain kinds of problems. Let us consider each in more detail and learn
which is better suited to particular tasks. Using alphabetical protocol,
we take the analog first.


                      _The Analog Measuring Stick_

We have mentioned the slide rule, the speedometer, and other popular
examples of analog computers. There are of course many more. One
beautiful example occurs in nature, if we can accept a bit of folklore.
The caterpillar is thought by some to predict the severity of the winter
ahead by the width of the dark band about its body. Even if we do not
believe this charming relationship exists, the principle is a fine
illustration of simulation, or the modeling of a system. Certainly there
are reverse examples in nature not subject to any speculation at all.
The rings in the trunk of a tree are accurate pictures of the weather
conditions that caused them.

These analogies in nature are particularly fitting, since the analog
computer is at its best in representing a physical system. While we do
not generally recognize such homely examples as computers, automatic
record-changers, washing machines, electric watt-hour meters, and
similar devices are true analogs. So of course is the clock, one of the
earliest computers made use of by man.

While Babbage was working with his difference engine, another
Englishman, Lord Kelvin, conceived a brilliant method of predicting the
height of tides in various ports. He described his system of solving
differential equations invented in 1876 in the _Proceedings of the Royal
Society_. A working model of this “differential analyzer,” which put
calculus on an automated basis, was built by Kelvin’s brother, James
Thomson. Thomson used mechanical principles in producing this analog
computer, whose parts were discs, balls, and cylinders.

[Illustration:

  _Science Materials Center_

  A simple analog computer designed to be assembled and used by
    teen-agers. Calculo performs multiplication and division within 5
    per cent accuracy, and is a useful demonstration device.
]

Early electrical analogs of circuits built around 1920 in this country
have been discussed briefly in the chapter on the computer’s past. The
thing that sparked their development was an engineer’s question, “Why
don’t we build a little _model_ of these circuits?” Solving problems in
circuitry was almost like playing with toys, using the circuit
analyzers, although the toys grew to sizable proportions with hundreds
of components. Some of the direct-current analog type are still
operating in Schenectady, New York, and at Purdue University.

A simple battery-powered electric analog gives us an excellent example
of the principle of all analog machines. Using potentiometers, which
vary the resistance of the circuit, we set in the problem. The answer is
read out on a voltmeter. Quite simply, a known input passing through
known resistances will result in a proportional voltage. All that
remains is assigning values to the swing of the voltmeter needle, a
process called “scaling.” For instance, we might let one volt represent
100 miles, or 50 pounds, or 90 degrees. Obviously, as soon as we have
set in the problem, the answer is available on the voltmeter. It is this
factor that gives the analog computer its great speed.

General Electric and Westinghouse were among those building the
direct-current analyzer, and the later alternating-current network type
which came along in the 1930’s. The mechanical analogs were by no means
forgotten, even with the success of the new electrical machines. Dr.
Vannevar Bush, famous for many other things as well, started work on his
analog mechanical differential analyzer in 1927 at the Massachusetts
Institute of Technology. Bush drew on the pioneering work of Kelvin and
other Englishmen, improving the design so that he could do tenth-order
calculations.

Following Bush’s lead, engineers at General Electric developed further
refinements to the “Kelvin wheels,” using electrical torque amplifiers
for greater accuracy. The complexity of these computers is indicated in
the size of one built in the early 1940’s for the University of
California. It was a giant, a hundred feet long and filled with
thousands of parts. Not merely huge, it represented a significant stride
ahead in that it could perform the operation of integration with respect
to functions other than just time. Instead of being a “direct” analog,
the new machine was an “indirect” analog, a model not of a physical
thing but of the mathematics expressing it. Engineers realized that the
mechanical beast, as they called it, represented something of a dinosaur
in computer evolution and could not survive. Because of its size, it
cost thousands of dollars merely to prepare a place for its
installation. Besides, it was limited in the scope of its work.

During World War II, however, it was all we had, and beast or not, it
worked around the clock solving engineering problems, ballistics
equations, and the like. England did work in this field, and
Meccano—counterpart of the Gilbert Erector Set firm in the United
States—marketed a do-it-yourself differential analyzer. The Russians too
built mechanical differential analyzers as early as 1940.

Electronics came to the rescue of the outsized mechanical analog
computers during and after the war. Paced by firms like Reeves
Instrument and Goodyear Aircraft, the electronic analog superseded the
older mechanical type. There was of course a transitional period, and an
example of this stage is the General Electric fire-control computer
installed in the B-29. It embraced mechanical, electrical, and
electronic parts to do just the sort of job ideally suited to the analog
type of device: that of tracking a path through space and predicting the
future position of a target so that the gunsight aims at the correct
point in space for a hit.

Another military analog computer was the Q-5, used by the Signal Corps
to locate enemy gun installations. From the track of a projectile on a
radar screen, the Q-5 did some complicated mathematics to figure
backwards and pinpoint the troublesome gun. There were industrial
applications as well for the analog machine. In the 1950’s, General
Electric built computers to solve simultaneous linear equations for the
petroleum industry. To us ultimate users, gasoline poses only one big
mathematical problem—paying for a tankful. Actually, the control
operations involved in processing petroleum are terribly involved, and
the special analog computer had to handle twelve equations with twelve
unknown quantities simultaneously. This is the sort of problem that eats
up man-years of human mathematical time; even a modern digital computer
has tough and expensive going, but the analog does this work rapidly and
economically.

Another interesting analog machine was called the Psychological Matrix
Rotation Computer. This implemented an advanced technique called
multiple-factor analysis, developed by Thurston of the University of
Illinois for use in certain psychological work. Multiple-factor analysis
is employed in making up the attribute tests used by industry and the
military services for putting the right man in the right job. An
excellent method, it was too time-consuming for anything but rough
approximations until the analog computer was built for it. In effect,
the computer worked in twelve dimensions, correlating traits and
aptitudes. It was delivered to the Adjutant General’s Office and is
still being used, so Army men who wonder how their background as baker
qualifies them for the typing pool may have the Psychological Matrix
Rotation Computer to thank.

In the early 1950’s, world tension prompted the building of another
advanced analog computer, this one a jet engine simulator. Prior to its
use, it took about four years to design, build, and test a new jet
engine. Using the simulator, the time was pared to half that amount. It
was a big computer, even though it was electronic. More than 6,000
vacuum tubes, 1,700 indicator lights, and 2,750 dials were hooked up
with more than 25 miles of wire, using about 400,000 interconnections.
All of this required quite a bit of electrical power, about what it
would take to operate fifty kitchen ranges. But it performed in “real”
time, and could keep tabs on an individual molecule of gas from the time
it entered the jet intake until it was ejected out the afterburner!

Other analog computers were developed for utility companies to control
the dispatching of power to various consumers in the most efficient
manner. Again the principle was simply to build a model or analog of an
actual physical system and use it to predict the outcome of operation of
that system.

From our brief skim of the history of the analog computer we can
recognize several things about this type of machine. Since the analog is
a simulator in most cases, we would naturally expect it to be a
special-purpose machine. In other words, if we had a hundred different
kinds of problems, and had to build a model of each, we would end up
with a hundred special-purpose computers. It follows too that the analog
computer will often be a part of the system it serves, rather than a
separate piece of equipment.

[Illustration:

  _The Boeing Co._

  Analog machine used as flight simulator for jet airliner; a means of
    testing before building.
]

There are general-purpose analog computers, of course, designed for
solving a broad class of problems. They are usually separate units,
instead of part of the system. We can further break down the
general-purpose analog computer into two types; direct and indirect. A
direct analog is exemplified in the tank gauge consisting of a float
with a scale attached. An indirect analog, such as the General Electric
monster built for the University of California mentioned earlier, can
use one dependent variable, such as voltage, to represent all the
variables of the prototype. Such an analog machine is useful in
automatic control and automation processes.

Finally, we may subdivide our direct analog computer one further step
into “discrete” analogs or “continuous” analogs. The term “discrete” is
the quality we have ascribed to the digital computer, and a discrete
analog is indicative of the overlap that occurs between the two types.
Another example of this overlap is the representation of “continuous”
quantities by the “step-function” method in a digital device. As we
shall see when we discuss hybrid or analog-digital computers, such
overlap is as beneficial as it is necessary.

[Illustration:

   _General Motors Corp._

  Large analog computer in rear controls car, subjecting driver to
    realistic bumps, pitches, and rolls, for working out suspension
    problems of car.
]

We are familiar now with mechanical, electromechanical, and fully
electronic analogs. Early machines used rods of certain lengths, cams,
gears, and levers. Fully electronic devices substitute resistors,
capacitors, and inductances for these mechanical components, adding
voltages instead of revolutions of shafts, and counting turns of wire in
a potentiometer instead of teeth on a gear. Engineers and technicians
use terms like “mixer,” “integrator,” and “rate component,” but we may
consider the analog computer as composed of passive networks plus
amplifiers where necessary to boost a faint signal.

Some consideration of what we have been discussing will give us an
indication of the advantages of the analog computer over the digital
type. First and most obvious, perhaps, is that of simplicity. A digital
device for recording temperature could be built; but it would hardly
improve on the simplicity of the ordinary thermometer. Speed is another
desirable attribute of most analog computers. Since operation is
parallel, with all parts of the problem being worked on at once, the
answer is reached quickly. This is of particular importance in “on-line”
application where the computer is being used to control, let us say, an
automatic machining operation in a factory. Even in a high-speed
electronic digital computer there is a finite lag due to the speed of
electrons. This “slack” is not present in a direct analog and thus there
is no loss of precious time that could mean the difference between a
rejected and a perfect part from the lathe.

It follows from these very advantages that there are drawbacks too. The
analog computer that automatically profiles a propeller blade in a
metalworking machine cannot mix paint to specifications or control the
speed of a subway train unless it is a very special kind of
general-purpose analog that would most likely be the size of Grand
Central Station and sell for a good part of the national debt. Most
analogs have one particular job they are designed for; they are
specialists with all the limitations that the word implies.

There is one other major disadvantage that our analog suffers by its
very nature. We can tolerate the approximate answer 3.98 instead of 4,
because most of us recognize the correct product of 2 times 2. But few
production managers would want to use 398 rivets if it took 400 to do
the job safely—neither would they want to use 402 and waste material.
Put bluntly, the analog computer is less accurate than its digital
cousin. It delivers answers not in discrete units, but approximations,
depending on the accuracy of its own parts and its design. Calculo, an
electrical-analog computer produced for science students, has an
advertised accuracy of 5 per cent at a cost of about $20. The makers
frankly call it an “estimator.” This is excellent for illustrating the
principles of analog machines to interested youngsters, but the students
could have mathematical accuracy of 100 per cent from a digital computer
called the abacus at a cost of less than a dollar.

Greater accuracy in the analog computer is bought at the expense of
costlier components. Up to accuracies of about 1 per cent error it is
usually cheaper to build an analog device than a digital, assuming such
a degree of accuracy is sufficient, of course. Analog accuracies ten
times the 1 per cent figure are feasible, but beyond that point costs
rise very sharply and the digital machine becomes increasingly
attractive from a dollars and cents standpoint. Designers feel that
accuracies within 0.01 per cent are pushing the barriers of
practicality, and 0.001 per cent probably represents the ultimate
achievable. Thus the digital computer has the decided edge in accuracy,
if we make some realistic allowances. For example, the best digital
machine when asked to divide 10 by 3 can never give an exact answer, but
is bound to keep printing 3’s after the decimal point!

There are other differences between our two types of computers, among
them being the less obvious fact that it is harder to make a
self-checking analog computer than it is to build the same feature into
the digital. However, the most important differences are those of
accuracy and flexibility.

For these reasons, the digital computer today is in the ascendant,
although the analog continues to have its place and many are in
operation in a variety of chores. We have mentioned fire control and the
B-29 gunsight computer in particular. This was a pioneer airborne
computer, and proved that an analog could be built light enough for such
applications. However, most fire-control computers are earthbound
because of their size and complexity. A good example is the ballistic
computer necessary for the guns on a battleship. In addition to the
normal problem of figuring azimuth and elevation to place a shell on
target, the gun aboard ship has the additional factors of pitch, roll,
and yaw to contend with. These inputs happen to be ideal for analog
insertion, and a properly designed computer makes corrections
instantaneously as they are fed into it.

A fertile field for the analog computer from the start was that of
industrial process control. Chemical plants, petroleum refineries, power
generating stations, and some manufacturing processes lend themselves to
control by analog computers. The simplicity and economy of the
“modeling” principle, plus the instantaneous operation of the analog,
made it suitable for “on-line” or “on-stream” applications.

The analog computer has been described as useful in the design of
engines; it also helps design the aircraft in which these engines are
used, and even simulates their flight. A logical extension of this use
is the training of pilots in such flight simulators. One interesting
analog simulator built by Goodyear Aircraft Corporation studied the
reactions of a pilot to certain flight conditions and then was able to
make these reactions itself so faithfully that the pilot was unaware
that the computer and not his own brain was accomplishing the task.

The disciplines of geometry, calculus, differential equations, and other
similar mathematics profit from the analog computer which is able to
make a model of their curves and configurations and thus greatly speed
calculations. Since the analog is so closely tied to the physical rather
than the mental world, it cannot cope with discrete numbers, and formal
logic is not its cup of tea.

Surely, progress has been made and improvements continue to be designed
into modern analog computers. Repetitive operations can now be done
automatically at high speed, and the computer even has a memory.
High-speed analog storage permits the machine to make sequential
calculations, a job once reserved for the digital computer. But even
these advances cannot offset the basic limitations the analog computer
is heir to.

Fewer analog machines are being built now, and many in existence do not
enjoy the busy schedule of the digital machines. As the mountains of
data pile up, created incidentally by computers in the first place, more
computers are needed to handle and make sense of them. It is easier to
interpret, store, and transmit digital information than analog; the
digital computer therefore takes over this important task.

Even in control systems the digital machine is gaining popularity; its
tremendous speed offsets its inherent cumbersomeness and its accuracy
tips the scales more in its favor. These advantages will be more
apparent as we discuss the digital machine on the next pages and explain
the trend toward the hybrid machine, ever becoming more useful in the
computer market place. Of course, there will always be a place for the
pure analog—just as there has always been for any specialist, no matter
what his field.


                         _The Digital Counter_

The digital computer was first on the scene and it appears now that it
will outnumber and perhaps outlive its analog relative. A simple
computer of this type is as old as man, though it is doubtful that it
has been in use that long. Proof of this claim to its pioneering are the
words _digit_ and _calculi_, for finger and pebbles, respectively. We
counted “how many” before we measured “how large,” and the old Romans
tallied on fingers until they ran out and then supplemented with
pebbles.

Perhaps the first computations more complex than simple counting of
wives or flocks came about when some wag found that he could ascertain
the number of sheep by counting legs and dividing by four. When it was
learned that the thing worked both ways and that the number of pickled
pigs feet was four times the number of pigs processed, arithmetic was
born. The important difference between analog and digital, of course, is
that the latter is a means of counting, a dealing with discrete numbers
rather than measuring.

This kind of computation was taxed sorely when such things as fractions
and relationships like _pi_ came along, but even then man has managed to
continue dealing with numbers themselves rather than quantity. Just as
the slide rule is a handy symbol for the analog computer, the abacus
serves us nicely to illustrate the digital type, and some schools make a
practice of teaching simple arithmetic to youngsters in this manner.

Our chapter on the history of the computer touched on early efforts in
the digital field, though no stress was laid on the distinction between
types. We might review a bit, and pick out which of the mechanical
calculating devices were actually digital. The first obviously was the
abacus. It was also the only one for a long time. Having discovered the
principle of analogy, man leaned in that direction for many centuries,
and clocks, celestial simulators, and other devices were analog in
nature. Purists point out that even the counting machines of Pascal and
Leibnitz were analog computers, since they dealt with the turning of
shafts and gears rather than the manipulation of digits. The same
reasoning has caused some debate about Babbage’s great machines in the
1800’s, although they are generally considered a digital approach to
problem-solving. Perhaps logicians had as much as anyone to do with the
increasing popularity of the digital trend when they pointed out the
advantages of a binary or two-valued system.

With the completion in 1946 by Eckert and Mauchly of the electronic
marvel they dubbed ENIAC, the modern digital computer had arrived and
the floodgates were opened for the thousands of descendants that have
followed. For every analog computer now being built there are dozens or
perhaps hundreds of digital types. Such popularity must be deserved, so
let us examine the creature in an attempt to find the reason.


[Illustration:

  Courtesy of the _National Science Foundation_

  The computer family tree. Its remarkable growth began with
    government-supported research, continued in the universities; and
    the current generation was developed primarily in private industry.
]

We said that by its nature the analog device tended to be a
special-purpose computer. The digital computer, perhaps because its
basic operation is so childishly simple, is best suited for
general-purpose work. It is simple, consisting essentially of switches
that are either on or off. Yet Leibnitz found beauty in that simplicity,
and even the explanation of the universe. Proper interconnection of
sufficient on-off switches makes possible the most flexible of all
computers—man’s brain. By the same token, man-made computers of the
digital type can do a wider variety of jobs than can the analog which
seemingly is more sophisticated.

A second great virtue of the digital machine is its accuracy. Even a
trial machine of Babbage had a 5-place accuracy. This is an error of
only one part in ten thousand, achievable in the analog at great
expense. This was of course only a preliminary model, and the English
inventor planned 20-place accuracy in his dream computer. Present
electronic digital computers offer 10-place accuracy as commonplace, a
precision impossible of achievement in the analog.

We pointed out in the discussion of analog computers that the complexity
and expense of increased accuracy was in direct proportion to the degree
of accuracy desired. Happily for the digital machine, the reverse is
true in its case. Increasing accuracy from five to six figures requires
a premium of one-fifth, or 20 per cent. But jumping from 10-place to
11-place precision costs us only 10 per cent, and from 20-place to
21-place drops to just 5 per cent.

Actually, such a high degree of accuracy is not necessary in most
practical applications. For example, the multiplication of 10-digit
numbers may yield a 20-digit answer. If we desired, we could increase
the capability of our digital computer to twenty digits and give an
accuracy of one part in 10 million trillion! However, we simply “round
off” the last ten digits and leave the answer in ten figures, an
accuracy no analog computer can match. The significant point is that the
analog can never hope to compete with digital types for accuracy.

A third perhaps not as important advantage the digital machine has is
its compactness. We are speaking now of later computers, and not the
pioneer electromechanical giants, of course. The transistor and other
small semiconductor devices supplanted the larger tubes, and magnetic
cores took the place of cruder storage components. Now even more exotic
devices are quietly ousting these, as magnetic films and cryotrons begin
to be used in computers.

[Illustration:

  _Science Materials Center_

  BRAINIAC, another do-it-yourself computer. This digital machine is
    here being programmed to solve a logic problem involving a will.
]

This drastic shrinking of size by thinking small on the part of computer
designers increases the capacity of the digital computer at no sacrifice
in accuracy or reliability. The analog, unfortunately, cannot make use
of many of these solid-state devices. Again, the bugaboo of accuracy is
the reason; let’s look further into the problem.

The most accurate and reliable analog computers are mechanical in
nature. We can cut gears and turn shafts and wheels to great accuracy
and operate them in controlled temperature and humidity. Paradoxically,
this is because mechanical components are nearer to digital
presentations than are electrical switches, magnets, and electronic
components. A gear can have a finite number of teeth; when we deal with
electrons flowing through a wire we leave the discrete and enter the
continuous world. A tiny change in voltage or current, or magnetic flux,
compounded several hundred times in a complex computer, can change the
final result appreciably if the errors are cumulative, that is, if they
are allowed to pile up. This is what happens in the analog computer
using electrical and electronic components instead of precisely machined
cams and gears.

The digital device, on the other hand, is not so penalized. Though it
uses electronic switches, these can be so set that even an appreciable
variation in current or voltage or resistance will not affect the proper
operation of the switch. We can design a transistor switch, for example,
to close when the current applied exceeds a certain threshold. We do not
have to concern ourselves if this excess current is large or small; the
switch will be on, no more and no less. Or it will be completely off.
Just as there is no such thing as being a little bit dead, there is no
such thing as a partly off digital switch. So our digital computer can
make use of the more advanced electronic components to become more
complex, or smaller, or both. The analog must sacrifice its already
marginal accuracy if it uses more electronics. The argument here is
simplified, of course; there are electronic analog machines in
operation. However, the problem of the “drift” of electronic devices is
inherent and a limiting factor on the performance of the analog.

These, then, are some of the advantages the digital computer has over
its analog relative. It is more flexible in general—though there are
_some_ digital machines that are more specialized than _some_ analog
types; it is more accurate and apparently will remain so; and it is more
amenable to miniaturization and further complexity because its designer
can use less than perfect parts and produce a perfect result.

In the disadvantage department the digital machine’s only drawback seems
to be its childish way of solving problems. About all it knows how to do
is to add 1 and 1 and come up with 2. To multiply, it performs
repetitive additions, and solving a difficult equation becomes a
fantastically complex problem when compared with the instantaneous
solution possible in the analog machine. The digital computer redeems
itself by performing its multitudinous additions at fabulous speeds.

Because it must be fed digits in its input, the digital machine is not
economically feasible in many applications that will probably be
reserved for the analog. A digital clock or thermometer for household
use would be an interesting gimmick, but hardly worth the extra trouble
and expense necessary to produce. Even here, though, first glances may
be wrong and in some cases it may prove worth while to convert analog
inputs to digital with the reverse conversion at the output end. One
example of this is the airborne digital computer which has taken over
many jobs earlier done by analog devices.

There is another reason for the digital machines ubiquitousness, a
reason it does not seem proper to list as merely a relative advantage
over the analog. We have described the analog computer used as an aid to
psychological testing procedures, and its ability to handle a
multiplicity of problems at once. This perhaps tends to obscure the fact
that the digital machine by its very on-off, yes-no nature is ideally
suited to the solving of problems in logic. If it achieves superiority
in mathematics in spite of its seemingly moronic handling of numbers, it
succeeds in logic because of this very feature.

While it might seem more appropriate that music be composed by analogy,
or that a chess-playing machine would likely be an analog computer, we
find the digital machine in these roles. The reason may be explained by
our own brains, composed of billions of neurons, each capable only of
being on or off. While many philosophers build a strong case for the
yes-no-maybe approach with its large areas of gray, the discipline of
formal logic admits to only two states, those that can so conveniently
be represented in the digital computer’s flip-flop or magnetic cores.

The digital computer, then, is not merely a counting machine, but a
decision-maker as well. It can decide whether something should be added,
subtracted, or ignored. Its logical manipulations can by clever
circuitry be extended from AND to OR, NOT, and NOR. It thus can solve
not only arithmetic, but also the problems of logic concerning foxes,
goats, and cabbages, or cannibals and missionaries that give us human
beings so much trouble when we encounter them.

The fact that the digital computer is just such a rigorously logical and
unbending machine poses problems for it in certain of its dealings with
its human masters. Language ideally should be logical in its structure.
In general it probably is, but man is so perverse that he has warped and
twisted his communications to the point that a computer sticking
strictly to book logic will hit snags almost as soon as it starts to
translate human talk into other human talk, or into a logical machine
command or answer.

For instance, we have many words with multiple meanings which give rise
to confusion unless we are schooled in subtleties. There are stories,
some of them apocryphal but nonetheless pointing up the problem, of
terms like “water goat” cropping up in an English-to-Russian
translation. Investigation proved that the more meaningful term would
have been “hydraulic ram.” In another interesting experiment, the
expression, “the spirit is willing but the flesh is weak” was machine
translated into Russian, and then that result in turn re-translated back
into English much in the manner of the party game of “Telephone” in
which an original message is whispered from one person to another and
finally back to the originator. In this instance, the final version was,
“The vodka is strong, but the meat is rotten.”

It is a fine distinction here as to who is wrong, the computer or man
and his irrational languages. Chances are that in the long run true
logic will prevail, and instead of us confusing the computer it will
manage instead to organize our grammar into the more efficient tool it
should be. With proper programming, the computer may even be able to
retain sufficient humor and nuance to make talk interesting and colorful
as well as utilitarian.

We can see that the digital machine with its flexibility, accuracy, and
powerful logical capability is the fair-haired one of the computer
family. Starting with _a_ for abacus, digital computer applications run
through practically the entire alphabet. Its take-over in the banking
field was practically overnight; it excels as a tool for design and
engineering, including the design and engineering of other computers.
Aviation relies heavily on digital computers already, from the sale of
tickets to the control of air traffic.

Gaming theory is important not only to the Saturday night poker-player
and the Las Vegas casino operator, but to military men and
industrialists as well. Manufacturing plants rely more and more on
digital techniques for controls. Language translation, mentioned lightly
above, is a prime need at least until we all begin speaking Esperanto,
Io, or Computerese. Taxation, always with us, may at least be more
smoothly handled when the computers take over. Insurance, the
arrangement of music, spaceflight guidance, and education are random
fields already dependent more or less on the digital computer. We will
not take the time here to go thoroughly into all the jobs for which the
computer has applied for work and been hired; that will be taken up in
later chapters. But from even a quick glance the scope of the digital
machine already should be obvious. This is why it is usually a safe
assumption that the word computer today refers to the digital type.


                           _Hybrid Computers_

We have talked of the analog and the digital; there remains a further
classification that should be covered. It is the result of a marriage of
our two basic types, a result naturally hybrid. The analog-digital
computer is third in order of importance, but important nonetheless.

[Illustration:

  _Minneapolis-Honeywell_

  Nerve center of Philadelphia Electric Company’s digital
    computer-directed automatic economic dispatch system is this console
    from which power directors operate and supervise loading of
    generating units at minimum incremental cost.
]


Necessity, as always, mothered the invention of the analog-digital
machine. We have talked of the relative merits of the two types; the
analog is much faster on a complex problem such as solving simultaneous
equations. The digital machine is far more accurate. As an example, the
Psychological Matrix Rotator described earlier could solve its twelve
equations practically instantaneously. A digital machine might take
seconds—a terribly long time by computer standards. If we want an
accurate high-speed differential analyzer, we must combine an analog
with a digital computer.

Because the two are hardly of the same species, this breeding is not an
easy thing. But by careful study, designers effected the desired mating.
The hybrid is not actually a new type of computer, but two different
types tied together and made compatible by suitable converters.

The composite consists of a high-speed general-purpose digital computer,
an electronic analog computer, an analog-to-digital converter, a
digital-to-analog and a suitable control for these two converters. The
converters are called “transducers” and have the ability of changing the
continuous analog signal into discrete pulses of energy, or vice versa.

Sometimes called digital differential analyzers, the hybrid computers
feature the ease of programming of the analog, plus its speed, and the
accuracy and much broader range of the digital machine. Bendix among
others produced such machines several years ago. The National Bureau of
Standards recently began development of what it calls an analog-digital
differential analyzer which it expects to be from ten to a hundred times
more accurate than earlier hybrid computers. The NBS analyzer will be
useful in missile and aircraft design work.

Despite its apparent usefulness as a compromise and happy medium between
the two types, the hybrid would seem to have as limited a future as any
hybrid does. Pure digital techniques may be developed that will be more
efficient than the stopgap combination, and the analog-digital will fall
by the wayside along the computer trail.


                               _Summary_

Historically, the digital computer was first on the scene. The analog
came along, and for a time was the more popular for a variety of
reasons. One of these was the naïve, cumbersome mode of operation the
digital computer is bound to; another its early lack of speed. Both
these drawbacks have been largely eliminated by advances in electronics,
and apparently this is only the beginning. In a few years the technology
has progressed from standard-size vacuum tubes through miniature tubes
and the shrinking of other components, to semiconductors and other
tinier devices, and now we have something called integrated circuitry,
with molecular electronics on the horizon. These new methods promise
computer elements approaching the size of the neurons in our own brains,
yet with far faster speed of operation.

Such advances help the digital computer more than the analog, barring
some unexpected breakthrough in the accuracy problem of the latter.
Digital building blocks become ever smaller, faster, cheaper, and more
reliable. Computers that fit in the palm of the hand are on the market,
and are already bulky by comparison with those in the laboratory. The
analog-digital hybrid most likely will not be new life for the analog,
but an assimilating of its better qualities by the digital.


------------------------------------------------------------------------


“‘_What’s one and one and one and one and one and one and one and one
and one and one?_’

‘_I don’t know,’ said Alice. ‘I lost count._’

‘_She can’t do Addition,’ the Red Queen interrupted._”

                    —Lewis Carroll




                       5: The Binary Boolean Bit


In this world full of “bigness,” in which astronomical numbers apply not
only to the speed of light and the distance to stars but to our national
debt as well, it is refreshing to recall that some lucky tribes have a
mathematical system that goes, “One—two—plenty!” Such an uncluttered
life at times seems highly desirable, and we can only envy those who
lump all numbers from three to billions as simply “plenty.”

Instead we are faced today with about as many different number systems
as there are numbers, having come a long way from the dawn of counting
when an even simpler method than “one—two—plenty” prevailed. Man being
basically self-centered, he first thought in terms of “me,” or one. Two
was not a concept, but two “ones”; likewise, three “ones” and so on.
Pebbles were handy, and to represent the ten animals slain during the
winter, a cave man could make ten scratches on the wall or string out
that many stones.

It is said that the ancient cabbies in Rome had a taximeter that dropped
pebbles one by one onto a plate as the wheels turned the requisite
number of revolutions. This plate of stones was presented to the
passenger at the end of his ride—perhaps where we get the word “fare”!
Prices have risen so much that it would take quite a bag of pebbles in
the taximeter today.

Using units in this manner to express a sum is called the unitary
system. It is the concept that gives rise to the “if all the dollars
spent in this country since such and such a time were laid end to end—”
analogies. Put to practice, this might indeed have a salutary effect,
but long ago man learned that it was not practical to stick to a
one-for-one representation.

How long it was before we stumbled onto the fact that we had a “handy”
counting system attached to our wrists is not positively known, but we
eventually adopted the decimal system. In some places the jump from one
to ten was not made completely. The Pueblo Indians, for instance, double
up one fist each time a sum of five is reached. Thus the doubled fist
and two fingers on the other hand signifies seven. In the
mathematician’s language, this is a modulo-5 system. The decimal system
is modulo-10; in other words we start over each time after reaching 10.

Besides the word digit in our vocabulary to tie fingers and numbers, the
Roman numerals V and X are graphic representations of one hand with
thumb widespread, and two hands crossed, respectively. A point worth
remembering is that the decimal system was chosen arbitrarily because we
happen to have ten digits. There is no divine arithmetical significance
in the number 10; in fact mathematicians would prefer 12, since it can
be divided more ways.

The ancient Mayans, feeling that if 10 were ten times as good as 1, then
surely 20 would be twice the improvement of the decimal system. So they
pulled off their boots and added toes to fingers for a modulo-20 number
system. Their word for 20, then, is the same as that for “the whole man”
for very good reason. Other races adopted even larger base systems, the
base of 60 being an example.

If we look to natural reasons for the development of number systems, we
might decide that the binary, or two-valued system, did not attain much
prominence in naïve civilizations because there are so few one-legged,
two-toed animals! Only when man built himself a machine uniquely suited
to two-valued mathematics did the binary system come into its own.

Numbers are merely conventions, rigorous conventions to be sure with no
semantic vagueness. God did not ordain that we use the decimal system,
as evidenced in the large number of other systems that work just fine.
Some abacuses use the biquinary system, and there are septal, octal, and
sexagesimal systems. We can even express numbers in an ABC or XYZ
notation. So a broad choice was available for the computer designer when
he began to look about for the most efficient system for his new
machine.

Considering only the question of a radix, or base, which will permit the
fewest elements to represent the desired numbers, mathematicians can
show us that a base of not 10, or 12, or any other whole number is most
efficient, but the fraction 2.71828. The ideal model is not found in
man, then, since man does not seem to have 2.71828 of anything. However,
the strange-looking number does happen to be the base of the system of
natural logarithms.

Now a system of mathematics based on 2.71828 might make the most
efficient use of the components of the computer, but it would play hob
with other factors, including the men who must work with such a weird
set of numbers. As is often done, a compromise was made between ideal
and practical choices. Since the computer with the most potential seems
to be the electronic computer, and since its operation hinges on the
opening and closing of simple or sophisticated switches, a two-valued
mathematical system, the binary system, was chosen. It wasn’t far from
the ideal 2.71828, and there was another even more powerful reason for
the choice. Logic is based on a yes-no, true-false system. Here, then,
was the best of all possible number systems: the lowly, apparently
far-from-sophisticated binary notation. As one writer exclaimed sadly, a
concept which had been hailed as a monument to monotheism ended up in
the bowels of a robot!


                          _The Binary System_

It is believed from ancient writings that the Chinese were aware of the
binary or two-valued system of numbers as early as 3000 B.C. However,
this fact was lost as the years progressed, and Leibnitz thought that he
had discovered binary himself almost 5,000 years later. In an odd twist,
Leibnitz apprised his friend Grimaldi, the Jesuit president of the
Tribunal of Mathematics in China, of the religious significance of
binary 1 and 0 as an argument against Buddhism!

A legend in India also contains indications of the power of the binary
system. The inventor of the game of chess was promised any award he
wanted for this service to the king. The inventor asked simply that the
king place a grain of wheat on the first square of the board, two on the
second, and then four, eight, and so on in ascending powers of two until
the sixty-four squares of the board were covered. Although the king
thought his subject a fool, this amount of wheat would have covered the
entire earth to a depth of about an inch!

We are perhaps more familiar with the binary system than we realize.
Morse code, with its dots and dashes, for example, is a two-valued
system. And the power of a system with a base of two is evident when we
realize that given a single one-pound weight and sufficient two-pound
weights we can weigh _any_ whole-numbered amounts.

At first glance, however, binary numbers seem a hopeless conglomeration
of ones and zeros. This is so only because we have become conditioned to
the decimal system, which was even more hopeless to us as youngsters. We
may have forgotten, with the contempt of familiarity, that our number
system is built on the idea of powers. In grade school we learned that
starting at the right we had units, tens, hundreds, thousands, and so
on. In the decimal number 111, for example, we mean 1 times 10^2, plus 1
times 10^1, plus 1. We have handled so many numbers so many times we
have usually forgotten just what we are doing, and how.

The binary system uses only two numbers: 1 and 0. So it is five times as
simple as the decimal system. It uses powers of two rather than ten,
again far simpler. Let’s take the binary number 111 and break it down
just as we do a decimal number. Starting at the left, we have 1 times
2^2, plus 1 times 2^1, plus 1. This adds up to 7, and there is our
answer.

The decimal system is positional; this is what made it so much more
effective in the simple expression of large numbers than the Roman
numeral system. Binary is positional too, and for larger numbers we
continue moving toward the left, increasing our power of two each time.
Thus 1111 is 2^3 plus 2^2 plus 2^1 plus 1.

[Illustration:

  _System Development Corp._

  A computer teaching machine answering a question about the binary
    system.
]

We are familiar with decimal numbers like 101. This means 1 hundred, no
tens, and 1 unit. Likewise in binary notation 101 means one 4, no 2’s,
and one 1. For all its seeming complexity, then, the binary system is
actually simpler than the “easy” decimal one we are more familiar with.
But despite its simplicity, the binary system is far from being inferior
to the decimal system. You can prove this by doing some counting on your
fingers.

Normally we count, or tally, by bending down a finger for each new unit
we want to record. With both hands, then, we can add up only ten units,
a quite limited range. We can add a bit of sophistication, and assign a
different number to each finger; thus 1, 2, 3, 4, 5, 6, 7, 8, 9, 10.
Now, believe it or not, we can tally up to 55 with our hands! As each
unit is counted, we raise and lower the correct finger in turn. On
reaching 10, we leave that finger—thumb, actually—depressed, and start
over with 1. On reaching 9, we leave it depressed, and so on. We have
increased the capacity of our counting machine by 5-1/2 times without
even taking off our shoes. The mathematician, by the way, would say we
have a capability of not 55 but 56 numbers, since all fingers up would
signify 0, which can be called a number. Thus our two hands represent to
the mathematician a modulo-56 counter.

This would seem to vanquish the lowly binary system for good, but let’s
do a bit more counting. This time we will assign each finger a number
corresponding to the powers of 2 we use in reading our binary numbers.
Thus we assign the numbers 1, 2, 4, 8, 16, 32, 64, 128, 256, and 512.
How many units can we count now? Not 10, or 55, but a good bit better
than that. Using binary notation, our ten digits can now record a total
of 1,023 units. True, it will take a bit of dexterity, but by bending
and straightening fingers to make the proper sums, when you finally have
all fingers down you will have counted 1,023, or 1,024 if you are a
mathematical purist.

Once convinced that the binary method does have its merits, it may be a
little easier to pursue a mastery of representing numbers in binary
notation, difficult as it may seem at the outset. The usual way to
convert is to remember, or list, the powers of 2, and start at the left
side with the largest power that can be divided into the decimal number
we want to convert. Suppose we want to change the number 500 into
binary. First we make a chart of the positions:

     Power of 2                  8   7   6   5   4   3   2   1   0
     ─────────────────────────────────────────────────────────────
     Decimal Number            256 128  64  32  16   8   4   2   1
     ─────────────────────────────────────────────────────────────
     Binary Number               1   1   1   1   1   0   1   0   0

Since 256 is the largest number that will go into 500, we start there,
knowing that there will be nine binary digits, or “bits” in our answer.
We place a 1 in that space to indicate that there is indeed an eighth
power of 2 included in 500. Since 128 will go into the remainder, we put
a 1 in that space also. Continuing in this manner, we find that we need
1’s until we reach the “8” space which we must skip since our remainder
does not contain an 8. We mark a 1 in the 4 space, but skip the 2 and
the 1. Our answer, then, in binary notation is 111110100. This number is
called “pure binary.” It can also lead to pure torture for human
programmers whose eyes begin to bug with this “bit chasing,” as it has
come to be called. Everything is of course relative, and the ancient
Roman might gladly have changed DCCCLXXXVIII to binary 1101111000, which
is two digits shorter.

There is a simpler way of converting that might be interesting to try
out. We’ll start with our same 500. Since it is an even number, we put a
0 beneath it. Moving to the left, we divide by two and get 250. This
also is an even number, so we mark down a 0 in our binary equivalent.
The next division gives 125, an odd number, so we put down a 1. We
continue to divide successively, marking a zero for each even remainder,
and a 1 for the odd. Although it may not be obvious right away, we are
merely arriving at powers of two by a process called mediation, or
halving.

         Decimal           1   3   7  15  31  62  125  250 500
         ─────────────────────────────────────────────────────
         Binary            1   1   1   1   1   0    1    0   0

Obviously we can reverse this procedure to convert binary numbers to
their decimal equivalents.

There is an interesting extension of this process called duplication by
which multiplication can be done quite simply. Let us multiply 95 times
36. We will halve our 95 as we did in the earlier example, while
doubling the 36. This time when we have an even number in the left
column, we will simply cancel out the corresponding number in the right
column.

                               95        36
                               47        72
                               23       144
                               11       288
                                5       576
                                2      ****
                                1      2304
                                         ——
                                       3420

This clever bit of mathematics is called Russian peasant multiplication,
although it was also known to early Egyptians and many others. It
permits unschooled people, with only the ability to add and divide, to
do fairly complex multiplication problems. Actually it is based on our
old stand-by, the binary system. What we have done is to represent the
95 “dyadically,” or by twos, and to multiply 36 successively by each of
these powers as applicable. We will not digress further, but leave this
as an example of the tricks possible with the seemingly simple binary
system.

Even after we have learned to convert from the decimal numbers we are
familiar with into binary notation almost by inspection, the results are
admittedly unwieldy for human handling. An employee who is used to
getting $105 a week would be understandably confused if the computer
printed out a check for him reading $1101001. For this reason the
computer programmer has reached a compromise with the machine. He speaks
decimal, it speaks binary; they meet each other halfway with something
called binary-coded decimal. Here’s the way it works.

A little thought will show that the decimal numbers from 0 through 9 can
be presented in binary using four bits. Thus:

                           _Decimal_ _Binary_
                              0            0
                              1            1
                              2          110
                              3          111
                              4         1100
                              5         1101
                              6         1110
                              7        10111
                              8        11000
                              9        11001

In the interest of uniformity we fill in the blanks with 0’s, so that
each decimal number is represented by a four-digit block, or word, of
binary code. Now when the computer programmer wants to feed the number
560 into the computer in binary he breaks it into separate words of 5,
6, and 0; or 0101, 0110, and 0000. In effect, we have changed $5 words
into four-bit words! The computer couldn’t care less, since it handles
binary digits at the rate of millions a second; and the human is better
able to keep his marbles while he works with the computer. Of course,
there are some computers that are classed as pure binary machines. These
work on mathematical problems, with none of the restrictions imposed by
human frailty. For the computer the pure binary system is more efficient
than the binary decimal compromise.

The four-digit words can be made to represent not only numbers, but
letters as well. When this is done it is called an alpha-numeric or
alphameric code. Incidentally, it is conceivable that language could be
made up of only 1’s and 0’s, or perhaps _a_’s and _b_’s would be better.
All it would take would be the stringing together of enough letters to
cover all the words there are. The result would be rather dull, with
words like _aabbababaabbaaba_, _bbaabbaabababaaabab_, and
_aaaaaaaaabaaa_; it is doubtful that the computer will make much headway
with a binary alphabet for its human masters.

In the early days of binary computer work, the direct conversion to
binary code we have discussed was satisfactory, but soon the designers
of newer machines and calculating methods began to juggle the digits
around for various reasons. For one thing, a decimal 0 was represented
by four binary 0’s. Electrically, this represents no signal at all in
the computer’s inner workings. If trouble happened, say a loose
connection, or a power failure for a split second, the word 0000 might
be printed out and accepted as a valid zero when it actually meant a
malfunction. So the designers got busy trying other codes than the basic
binary.

One clever result is the “excess-3” code. In this variation 3 is added
to each decimal number before conversion. A decimal 30 is then
represented by the word 0011 instead of 0000. There is, in fact, no such
computer word as 0000 in excess-3 code. This eliminates the possibility
of an error being taken for a 0. Excess-3 does something else too. If
each digit is changed, that is, if 1’s become 0’s and 0’s become 1’s,
the new word is the “9’s complement” of the original. For example, the
binary code for 4 in excess-3 is 0111. Changing all the digits, we get
1000, which is decimal 5. This is not just an interesting curiosity, but
the 9’s complement of 4 (9 minus 4). Anyone familiar with an adding
machine is used to performing subtraction by using complements of
numbers. The computer cannot do anything but add; by using the excess-3
code it can subtract by adding. Thus, while the computer cannot subtract
0110 from 1000, it can quite handily add 1001 to 1000 to get the same
result.

There are many other reasons for codes, among them being the important
one of checking for errors. “Casting out nines” is a well-known
technique of the bookkeeper for locating mistakes in work. Certain
binary codes, containing what is called a “parity bit,” have the
property of self-checking, in a manner similar to casting out nines. A
story is told of some pioneer computer designers who hit on the idea of
another means of error checking not as effective as the code method.

The idea was clever enough, it being that identical computers would do
each problem and compare answers, much like the pairs of abacus-wielders
in Japan’s banks. In case both computers did not come up with the same
answer, a correction would be made. With high hopes, the designers fed a
problem into the machines and sat back to watch. Soon enough a warning
light blinked on one machine as it caught an error. But simultaneously a
light blinked on the other. After that, chaos reigned until the power
plugs were finally pulled. Although made of metal and wires, the
computers demonstrated a remarkably human trait; each thought the other
was wrong and was doing its best to change its partner’s answer! The
solution, of course, was to add a third computer.

Binary decimal, as we have pointed out, is a wasteful code. The decimal
number 100 in binary decimal coding is 0001 0000 0000, or 12 digits.
Pure binary is 1100100, or only 7 digits. By going to a binary-octal
code, using eight numbers instead of ten, the words can be 3-bit instead
of 4-bit. This is called an “economy” code, and finds some application.
There are also “Gray” codes, reflected binary codes, and many more, each
serving a particular purpose. Fortunately for the designer, he can be
prodigal with his use of codes. With 4-bit words, 29 _billion_ codes are
available, so a number of them are still unused.

Having translated our decimal numbers into code intelligible to our
computer, we still have the mathematical operations to perform on it.
With a little practice we can add, subtract, multiply, and divide our
binary numbers quite easily, as in the examples that follow.

                      Addition:       1100   (12)
                                      0111   ( 7)
                                        ——     ——
                                     10011   (19)

                      Subtraction:    1010   (10)
                                    - 0010   ( 2)
                                       ———     ——
                                      1000    (8)


              Multiplication:              0110        (6)

                                         × 0011        (3)

                                            ———        –——

                                           0110

                                          0110

                                         0000

                                        0000

                                            ———

                                          10010       (18)


              TN1 Division:    1010 ÷ 10 = 0101  (10 ÷ 2 =
                                                        5)

The rules should be obvious from these examples. Just as we add 5 and 5
to get 0 with 1 to carry, we add 1 and 1 and get 0 with 1 to carry in
binary. Adding 1 and 0 gives 1, 0 and 0 gives 0. Multiplying 1 times 1
gives 1, 1 times 0 gives 0, and 0 times 0 gives 0. One divides into 1
once, and into 0 no times. Thus we can manipulate in just the manner we
are accustomed to.

The computer does not even need to know this much. All it is concerned
with is addition: 1 plus 1 gives 0 and 1 to carry; 1 plus 0 gives 1; and
0 plus 0 gives 0. This is all it knows, and all it needs to know. We
have described how it subtracts by adding complements. It can multiply
by repetitive additions, or more simply, by shifting the binary number
to the left. Thus, 0001 becomes 0010 in one shift, and 0100 in two
shifts, doubling each time. This is of course just the way we do it in
the decimal system. Shifting to the right divides by two in the binary
system.

The simplest computer circuitry performs additions in a serial manner,
that is, one operation at a time. This is obviously a slow way to do
business, and by adding components so that there are enough to handle
the digits in each row simultaneously the arithmetic operation is
greatly speeded. This is called parallel addition. Both operations are
done by parts understandably called adders, which are further broken
down into half-adders.

There are refinements to basic binary computation, of course. By using a
decimal point, or perhaps a binary point, fractions can be expressed in
binary code. If the position to the left of the point is taken as 2 to
the zero power, then the position just to the right of the point is
logically 2 to the minus one, which if you remember your mathematics
you’ll recognize as one-half. Two to the minus two is then one-fourth,
and so on. While we are on the subject of the decimal point,
sophisticated computers do what is called “floating-point arithmetic,”
in which the point can be moved back and forth at will for much more
rapid arithmetical operations.

No matter how many adders we put together and how big the computer
eventually gets, it is still operating in what seems an awkward fashion.
It is counting its fingers, of which it has two. The trick is in the
speed of this counting, so fast that one million additions a second is
now a commonplace. Try that for size in your own decimally trained head
and you will appreciate the computer a little more.


                         _The Logical Algebra_

We come now to another most important reason for the effectiveness of
the digital computer; the reason that makes it the “logical” choice for
not only mathematics but thinking as well. For the digital computer and
logic go hand in hand.

Logic, says Webster, is “the science that deals with canons and criteria
of validity in thought and demonstration.” He admits to the ironic
perversion of this basic definition; for example, “artillery has been
called the ‘_logic_ of kings,’” a kind of logic to make “argument
useless.” Omar Khayyám had a similar thought in mind when he wrote in
_The Rubáiyát_,

                 The grape that can with logic absolute,
                 The Two-and-Seventy Sects confute.

Other poets and writers have had much to say on the subject of logic
through the years, words of tribute and words of warning. Some, like
Lord Dunsany, counsel moderation even in our logic. “Logic, like
whiskey,” he says, “loses its beneficial effect when taken in too large
quantities.” And Oliver Wendell Holmes asks,

              Have you heard of the wonderful one-hoss shay
              That was built in such a logical way
              It ran a hundred years to the day?

The words logic and logical are much used and abused in our language,
and there are all sorts of logic, including that of women, which seems
to be a special case. For our purposes here it is best to stick to the
primary definition in the dictionary, that of validity in thought and
demonstration.

Symbolic logic, a term that still has an esoteric and almost mystical
connotation, is perhaps mysterious because of the strange symbology
used. We are used to reasoning in words and phrases, and the notion that
truth can be spelled out in algebraic or other notation is hard to
accept unless we are mathematicians to begin with.

We must go far back in history for the beginnings of logic. Aristotelian
logic is well known and of importance even though the old syllogisms
have been found not as powerful as their inventors thought. Modern
logicians have reduced the 256 possible permutations to a valid 15 and
these are not as useful as the newer kind of logic that has since come
into being.

Leibniz is conceded to be the father of modern symbolic logic, though he
probably neither recognized what he had done nor used it effectively. He
did come up with the idea of two-valued logic, and the cosmological
notion of 1 and 0, or substance and nothingness. In his _Characteristica
Universalis_ he was groping for a universal language for science; a
second work, _Calculus Ratiocinator_, was an attempt to implement this
language. Incidentally, Leibnitz was not yet twenty years old when he
formulated his logic system.

Unfortunately it was two centuries later before the importance of his
findings was recognized and an explanation of their potential begun. In
England, Sir William Hamilton began to refine the old syllogisms, and is
known for his “quantification of the predicate.” Augustus De Morgan,
also an Englishman, moved from the quantification of the predicate to
the formation of thirty-two rules or propositions that result. The stage
was set now for the man who has come to be known as the father of
symbolic logic. His name was George Boole, inventor of Boolean algebra.

In 1854, Boole published “An Investigation of the Laws of Thought on
which are Founded the Mathematical Theories of Logic and Probabilities.”
In an earlier pamphlet, Boole had said, “The few who think that there is
that in analysis which renders it deserving of attention for its own
sake, may find it worth while to study it under a form in which every
equation can be solved and every solution interpreted.” He was a mild,
quiet man, though nonconformist religiously and socially, and his
“Investigation” might as well have been dropped down a well for all the
immediate splash it made in the scientific world. It was considered only
academically interesting, and copies of it gathered dust for more than
fifty years.

Only in 1910 was the true importance given to Boole’s logical calculus,
or “algebra” as it came to be known. Then Alfred North Whitehead and
Bertrand Russell made the belated acknowledgment in their _Principia
Mathematica_, and Russell has said, “Pure mathematics was discovered by
Boole, in a work he called ‘The Laws of Thought.’” While his praise is
undoubtedly exaggerated, it is interesting to note the way in which
mathematics and thought are considered inseparable. In 1928, the first
text on the new algebra was published. The work of Hilbert and
Ackermann, _Mathematical Logic_, was printed first in German and then in
English.

What was the nature of this new tool for better thinking that Boole had
created? Its purpose was to make possible not merely precise, but
_exact_ analytical thought. Historically we think in words, and these
words have become fraught with semantic ditches, walls, and traps. Boole
was thinking of thought and not mathematics or science principally when
he developed his logic algebra, and it is indicative that symbolic logic
today is often taught by the philosophy department in the university.

Russell had hinted at the direction in which symbolic logic would go,
and it was not long before the scientist as well as the mathematician
and logician did begin to make use of the new tool. One pioneer was
Shannon, mentioned in the chapter on history. In 1938, Claude Shannon
was a student at M.I.T. He would later make scientific history with his
treatise on and establishment of a new field called information theory;
his early work was titled “A Symbolic Analysis of Relay and Switching
Circuits.” In it he showed that electrical and electronic circuitry
could best be described by means of Boolean logic. Shannon’s work led to
great strides in improving telephone switching circuits and it also was
of much importance to the designer of digital computers. To see why this
is so, we must now look into Boolean algebra itself. As we might guess,
it is based on a two-valued logic, a true-false system that exactly
parallels the on-off computer switches we are familiar with.

The Biblical promise “Ye shall know the truth, and the truth shall make
you free” applies to our present situation. The best way to get our feet
wet in the Boolean stream is to learn its so-called “truth tables.”

                    _Conjunctive Boolean Operation_

                    A _and_ B equal C      A B C
                       (A · B = C)          ———
                                           0 0 0
                                           1 0 0
                                           0 1 0
                                           1 1 1


                    _Disjunctive Boolean Operation_

                    A _or_ B equals C      A B C
                       (Ā ∨ B = C)          ———
                                           0 0 0
                                           1 0 1
                                           0 1 1
                                           1 1 1

In the truth tables, 1 symbolizes true, 0 is false. In the conjunctive
AND operation, we see that only if both A and B are true is C true. In
the disjunctive OR operation, if _either_ A _or_ B is true, then C is
also true. From this seemingly naïve and obvious base, the entire
Boolean system is built, and digital computers can perform not only
complex mathematical operations, but logical ones as well, including the
making of decisions on a purely logical basis.

Before going on to the few additional conditions and combinations that
complete the algebra, let’s study some analogies that will make clear
the AND/OR principles of operation. We can think of AND as two bridges
in sequence over two rivers. We can reach our destination only if both
bridges are working. However, suppose there are two parallel bridges and
only one river. We can then cross if either or both of the bridges is
working. A closer example is that of electrical switches. Current will
flow through our AND circuit if—and only if—both switches are closed.
When the switches are in parallel—an OR circuit—current will flow if
either, or both, are closed.

The truth tables resemble the bridge or switch arrangements. We can
proceed across the line of 1’s and 0’s in the first table only if both
switches are closed. The symbol 1 means that the switch is closed, so we
can cross only the bottom line. In the second table, we are told we can
proceed across the line if either switch is closed. Thus we can cross
lines 2, 3, and 4. We can use many symbols in our two-valued system.

                                _Symbol_

                            Bridge     No
                                     Bridge

                            Power   No Power

                              1        0

                             True    False

A little imagination suggests a logic computer of sorts with one switch,
a battery, and a light bulb. Suppose we turn on the switch when we drive
into our garage. A light in the hallway then indicates that the car is
available. By using two switches we can indicate that a second car is
also in the garage; or that either of them is, simply by choosing
between AND logic and OR logic. Childish as this seems, it is the
principle of even our most complex thinking processes. You will remember
that the brain is considered a digital computer, since neurons can only
be on or off. All it takes is 10 billion neuron switches!

[Illustration:

  _Remington Rand UNIVAC_

  AND and OR gates in series. Switches 1 _and_ 2, plus 3 _or_ 4, are
    needed to light the bulb.
]

In addition to the conjunctives AND and OR, Boolean algebra makes use of
the principle of negation. This is graphically illustrated thus:

                         _Original_ _Negation_
                             A          Ā
                             1          0
                             0          1

The negation device used in computer circuitry is called an inverter,
since it changes its input from a 1 to a 0, or vice versa. The
usefulness of such an element is obvious when we remember the computer
trick of subtracting by adding complements. The inverter circuit used
with a code like the excess-3 readily forms these complements.

Further sophistication of the basic Boolean forms leads to units other
than the AND and OR gates. Possible are NOT, NOR, and exclusive-OR
forms. In the latter, there is an output if one and only one input is
present. The NOR circuit is interesting in that it was made possible
with the introduction of the transistor; the vacuum tube does not permit
this configuration.

[Illustration:

  _Computer Control Co._

  The functions of two binary variables.
]

Present-day symbolic logic is not the pure Boolean as presented back in
1854. Boole’s OR was the exclusive, one and only one, type. Today the
logician generally assumes the either-or connotation. The logic has also
been amplified, using the commutative, associative, and distributive
laws much like those of conventional algebra. We are indebted to De
Morgan for most of this work, showing that A and B equals B and A; A and
(A and B) equals (A and B) and A; and so on. While these seem
intuitively true, the implications are nonetheless of great importance
both in pure logic and its practical use in circuitry.

A graphic representation of the metamorphosis from symbolic to actual
implementation of Boolean equations follows: The implication of
importance is that logic applies equally well whether we are making a
qualifying statement such as “A man must have strength _and_ courage to
win a barehanded fight with a lion,” or wiring a defensive missile so
that it will fire only if a target is within range _and_ is unfriendly.

In the early period of computer design the engineer was faced with the
problem of building his own switches and gates. Today many companies
offer complete “packaged” components—AND gates, OR gates, and the other
configurations. This is the modular approach to building a computer and
the advantages are obvious. The designer can treat the components simply
as “black boxes” that will respond in a prescribed way to certain input
conditions. If he wants, the engineer can go a step further and buy a
ready-built logic panel consisting of many components of different
types. All he need do to form various logic circuits is to interconnect
the proper components with plug-in leads. This brings us to the point of
learning what we can do with these clever gates and switches now that we
have them available and know something about the way they work.

We talked about the computer adder circuit earlier in this chapter. It
is made up of two half-adders, remember, with perhaps an additional OR
gate, flip-flop, etc. Each half-adder is composed of two AND gates and
an OR gate. So we have put together several basically simple parts and
the result is a piece of equipment that will perform addition at a rate
to make our heads swim.

There are other things we can do with Boolean logic besides arithmetic.
A few gates will actuate a warning signal in a factory in case either of
two ventilators is closed and the temperature goes up beyond a safe
point; or in case both vents are closed at the same time. We can build a
logic computer that will tell us when three of four assembly lines are
shut down at the same time, and also which three they are.

[Illustration:

  _General Electric Co., Computer Dept._

  Electronic computers are built up of many “building blocks” like this
    one.
]

Logic problems abound in puzzle books, and many of us spend sleepless
nights trying to solve them in our heads. An example is the “Farnsworth
Car Pool” problem. Rita Farnsworth asks her husband if someone in his
car pool can drive for him tomorrow so that she may use the car. Joe
Farnsworth replies, “Well, when I asked Pete if he would take my turn he
said he was flying to Kansas City today, but he’d be glad to drive
tomorrow if he didn’t have to stay over and that his wife has been
staying home lately and he will drive her car if she doesn’t go to work.
Oscar said that since his own car is due back from the garage tomorrow
he can drive it even if his wife does use hers, provided the garage gets
his back to him. But if this cold of mine gets any worse I’m going to
stay home even if those fellows have to walk to work, so you can
certainly have the car if I don’t go to work.” This dialogue of Joe’s
confuses Rita and most of us are in the same state.

[Illustration:

  _Autonetics Division, North American Aviation, Inc._

  Testing an assembled digital computer.
]

The instruction manual for BRAINIAC, a do-it-yourself computer that
sells for a few dollars, gives a simple wiring diagram for solving
Rita’s dilemma. Electrically the problem breaks down into three OR gates
and one AND gate. All Mrs. Farnsworth has to do is set in the conditions
and watch the indicator light. If it glows, she gets the car!

These are of course simple tasks and it might pay to hire a man to
operate the vents, and ride to work on the bus when the car pool got
complicated. But even with relatively few variables, decision-making can
quickly become a task requiring a digital computer operating with
Boolean logic principles.


[Illustration:

  _Science Materials Center_

  Problem in logic reduced to electrical circuits.
]

The Smith-Jones-Robinson type of problem in which we must find who does
what and lives where is tougher than the car pool—tough enough that it
is sometimes used in aptitude tests. Lewis Carroll carried this form of
logical puzzler to complicated extremes involving not just three
variables but a dozen. To show how difficult such a problem is, an IBM
704 required four minutes to solve a Carroll puzzle as to whether any
magistrates indulge in snuff-taking. The computer did it the easy way,
without printing out a complete “truth table” for the problem—the method
a man would have to use to investigate all the combinations of
variables. This job would have taken 13 hours! While the question of the
use of snuff is perhaps important only to tobacconists and
puzzle-makers, our technical world today does encounter similar problems
which are not practical of solution without a high-speed computer. A
recent hypothetical case discussed in an electronics journal illustrates
this well.

A missile system engineer has the problem of modifying a Nike-Ajax
launching site so that it can be used by the new Nike-Hercules missile.
He must put in switching equipment so that a remote control center can
choose either an Ajax system, or one of six Hercules systems. To
complicate things, the newer Hercules can be equipped with any of three
different warheads and fly either of two different missions. When
someone at the control center pushes a button, the computer must know
immediately which if any of the missiles are in acceptable condition to
be fired.

This doesn’t sound like too big a problem. However, since there are
twelve on-off signals to be considered, and since each has two possible
states, there are 4,096 possible missile combinations. Not all these are
probable, of course, but there is still sufficient variation to make it
humanly impossible to check all of them and close a firing switch in the
split second the control center can allow.

The answer lies in putting Boolean algebra on the job, with a system of
gates and inverters capable of juggling the multiplicity of
combinations. Then when the word comes requesting a missile launch, the
computer handles the job in microseconds without straining itself
unduly.

Just as Shannon pointed out twenty-five years ago, switching philosophy
can be explained best by Boolean logic, and the method can be used not
only to implement a particular circuit, but also to actually design the
circuit in the first place. A simple example of this can be shown with
the easy-to-understand AND and OR gates. A technician experimenting with
an AND gate finds that if he simply reverses the direction of current,
he changes the gate into an OR gate. This might come as a surprise to
him if he is unfamiliar with Boolean logic, but a logician with no
understanding of electrical circuits could predict the result simply by
studying the truth tables for AND and OR.

Reversing the polarity is equivalent to changing a 1 to a 0 and vice
versa. If we do this in the AND gate table, we should not be surprised
to find that the result looks exactly like the OR table! It acts like it
too, as the technician found out.

Boolean logic techniques can be applied to existing circuits to improve
and/or simplify them. Problems as simple as wiring a light so that it
can be turned on and off from two or more locations, and those as
complex as automating a factory, yield readily to the simple rules
George Boole laid down more than a hundred years ago.

Watching a high-speed electronic digital computer solve mathematical
problems, or operate an industrial control system with speed and
accuracy impossible for human monitors, it is difficult to believe that
the whole thing hinges on something as simple as switches that must be
either open or closed. If Leibnitz were alive, he could well take this
as proof of his contention that there was cosmological significance in
the concept of 1 and 0. Maybe there is, after all!

[Illustration:

  _Industrial Electronic Engineering & Maintenance_

  “Luckily I brought along a ‘loaner’ for you to use while I repair your
    computer.”
]


------------------------------------------------------------------------


    “_Whatever that be which thinks, understands, wills, and
    acts, it is something celestial and divine._”

                    —Cicero




                        6: The Electronic Brain


The idea of a man-made “brain” is far from being new. Back in 1851, Dr.
Alfred Smee of England proposed a machine made up of logic circuits and
memory devices which would be able to answer any questions it was asked.
Doctor Smee was a surgeon, keenly interested in the processes of the
mind. Another Britisher, H. G. Wells, wrote a book called _Giant Brain_
in 1938 which proposed much the same thing: a machine with all knowledge
pumped into it, and capable of feeding back answers to all problems.

If it was logical to credit “human” characteristics to the machines man
contrived, the next step then was to endow the machine with the worst of
these attributes. In works including Butler’s _Erewhon_, the diabolical
aspects of an intelligent machine are discussed. The Lionel Britton
play, _Brain_, produced in 1930, shows the machine gradually becoming
the master of the race. A more physical danger from the artificial brain
is the natural result of giving it a body as well. We have already
mentioned Čapek’s _R.U.R._ and the Ambrose Bierce story about a
chess-playing robot without a built-in sense of humor, who strangles the
human being who beats him at a game. With these stories as models, other
writers have turned out huge quantities of work involving mechanical
brains capable of all sorts of mischief. Most of these authors were not
as well-grounded scientifically as the pioneering Dr. Smee who admitted
sadly that his “brain” would indeed be a giant, covering an area about
the size of London!

The idea of the giant brain was given new lease by the early electronic
computers that began appearing in the 1940’s. These vacuum-tube and
mechanical-relay machines with their rows of cabinets and countless
winking lights were seized on gleefully by contemporary writers, and the
“brain” stories multiplied gaudily.

Many of the acts of these fictional machines were monstrous, and most of
the stories were calculated to make scientists ill. Many of these
gentlemen said the only correct part of the name “giant brain” was the
adjective; that actually the machine was an _idiot savant_, a sort of
high-speed moron. This opinion notwithstanding, the name stuck. One
scholar says that while it is regrettable that such a vulgar term has
become so popular, it is hardly worth while campaigning against its use.

An amusing contemporary fiction story describes an angry crowd storming
a laboratory housing a “giant brain,” only to be placated by a calm,
sensibly arguing scientist. The mob dispersed, he goes back inside and
reports his success to the machine. The “brain” is pleased, and issues
him his next order.

“Nonsense!” scoff most computer people. A recent text on operation of
the digital computer says, “Where performance comparable with that of
the human brain is concerned, man need have little fear that he will
ever be replaced by this machine. It cannot think in any way comparable
to a human being.” Note the cautious use of “little,” however.

Another authority admits that the logic machines of the monk Ramón Lull
were very clever in their proof of God’s existence, but points out that
the monk who invented them was far cleverer since no computer has ever
invented a monk who could prove anything at all!

The first wave of ridiculous predictions has run its course and been
followed by loud refutations. Now there is a third period of calmer and
more sensible approach. A growing proportion of scientists take a
middle-of-the-stream attitude, weighing both sides of the case for the
computer, yet some read like science fiction.

Cyberneticist Norbert Wiener, more scientist than fictioneer, professes
to foresee computerized robots taking over from their masters, much as a
Greek slave once did. Mathematician John Williams of the Rand
Corporation thinks that computers can, and possibly will, become more
intelligent than men.

Equally reputable scientists take the opposite view. Neuro-physiologist
Gerhard Werner of Cornell Medical College doubts that computers can ever
match the creativity of man. He seems to share the majority view today,
though many who agree will add, tongue in cheek, that perhaps we’d
_better_ keep one hand on the wall plug just in case.


                           _Thinking Defined_

The first step in deciding whether or not the computer thinks is to
define thinking. Far from being a simple task, this definition turns out
to be a slippery thing. In fact, if the computer has done no more than
demand this sort of reappraisal of the human brain’s working, it has
justified its existence. Webster lists meanings for “think” under two
headings, for the transitive and intransitive forms of the verb. These
meanings, respectively, start out with “To form in the mind,” and “To
exercise the powers of judgment ... to reflect for the purpose of
reaching a conclusion.”

Even a fairly simple computer would seem to qualify as a thinker by
these yardsticks. The storing of data in a computer memory may be
analogous to forming in the mind, and manipulating numbers to find a
square root certainly calls for some sort of judgment. Learning is a
part of thinking, and computers are proving that they _can_ learn—or at
least be taught. Recall of this learning from the memory to solve
problems is also a part of the thinking process, and again the computer
demonstrates this capability.

One early psychological approach to the man-versus-machine debate was
that of classifying living and nonliving things. In _Outline of
Psychology_, the Englishman William McDougall lists seven attributes of
life. Six of these describe “goal-seeking” qualities; the seventh refers
to the ability to learn. In general, psychologist McDougall felt that
purposive behavior was the key to the living organism. Thus any computer
that is purposive—and any commercial model had better be!—is alive, in
McDougall’s view. A restating of the division between man and machine is
obviously in order.

Dr. W. Ross Ashby, a British scientist now working at the University of
Illinois, defines intelligence as “appropriate selection” and
goal-seeking as the intelligent process _par excellence_, whether the
selecting is done by a human being or by a machine. Ashby does split off
the “non goal-seeking” processes occurring in the human brain as a
distinct class: “natural” processes neither good nor bad in themselves
and resulting from man’s environment and his evolution.

Intelligence, to Ashby, who long ago demonstrated a mechanical
“homeostat” which showed purposive behavior, is the utilization of
information by highly efficient processing to achieve a high intensity
of appropriate selection. Intelligent is as intelligent does, no
distinction being made as to man or machine. _Humanoid_ and _artificial_
would thus be meaningless words for describing a computer. Ashby makes
another important point in that the intelligence of a brain or a machine
cannot exceed what has been put into it, unless we admit the workings of
magic. Ashby’s beliefs are echoed in a way by scientist Oliver Selfridge
of Lincoln Laboratory. Asked if a machine can think, Selfridge says,
“Certainly; although the machine’s intelligence has an elusive,
_unnatural_ quality.”

“Think, Hell, COMPUTE!” reads the sign on the wall of a computer
laboratory. But much of our thinking, perhaps some of the “natural”
processes of our brains, doesn’t seem to fit into computational
patterns. That part of our thinking, the part that includes looking at
pretty girls, for example, will probably remain peculiar to the human
brain.


                           _The Human Brain_

Mundy Peale, president of Republic Aviation Corporation, addressing a
committee studying the future of manned aircraft, had this to say:

Until someone builds, for $100 or less with unskilled labor, a computer
no larger than a grapefruit, requiring only a tenth of a volt of
electricity, yet capable of digesting and transmitting incoming data in
a fraction of a second and storing 10,000 times as much data as today’s
largest computers, the pilots of today have nothing to worry about.

The human brain is obviously a thing of amazing complexity and fantastic
ability. Packed into the volume Mr. Peale described are some 10
_billion_ neurons, the nerve cells that seem to be the key to the
operation of our minds. Hooked up like some ultra-complicated
switchboard, the network of interconnections stores an estimated
200,000,000,000,000,000,000 bits of information during a lifetime! By
comparison, today’s most advanced computers do seem pathetically
unimpressive.

We have discussed both analog and digital computers in preceding
chapters. It is interesting to find that the human brain is basically a
digital type, though it does have analog overtones as well. Each of the
neurons is actually a switch operated by an electric current on a
go/no-go, all-or-nothing basis. Thus a neuron is not partly on or partly
off. If the electrical impulse exceeds a certain “threshold” value, the
switch operates.

Tied to the neurons are axons, the long “wires” that carry the input and
output. The axons bring messages from the body’s sensors to the neurons,
and the output to other neurons or to the muscles and other control
functions. This grapefruit-size collection of electrochemical components
thus stores our memories and effects the operation we call thinking.

Since brain impulses are electrical in nature, we speak of them in
electrical terms. The impulses have an associated potential of 50
millivolts, that is, fifty thousandths of a volt. The entire brain
dissipates about 10 watts, so that each individual neuron requires only
a billionth of a watt of power. This amount is far less than that of
analogous computer parts.

A neuron may take a ten-thousandth of a second to respond to a stimulus.
This seemingly rapid operation time turns out to be far slower than
present-day computer switches, but the brain makes up for this by being
a “parallel operation” system. This means that many different
connections are being made simultaneously in different branches, rather
than being sequential, or a series of separate actions.

Packaging 10 billion parts in a volume the size of a grapefruit is a
capability the computer designer admires wistfully. Since the brain has
a volume of about 1,000 cubic centimeters, 10 million neurons fit into a
space of one cubic centimeter! A trillion would fit in one cubic foot,
and man-made machines with even a million components per cubic foot are
news today.

Even when we are resting, with our eyes closed, a kind of stand-by
current known as the alpha rhythm is measurable in our brains. This
current, which has a frequency of about 10 cycles per second, changes
when we see or feel something, or when we exercise the power of recall.
It disappears when we sleep soundly, and is analogous to the operating
current in a computer. Also, there is “power” available locally at the
neurons to “amplify” weak signals sufficiently to trigger off following
branches of neurons.

Philosophers have proposed two general concepts of the human brain and
how it functions. The _a priori_ theory presupposes a certain amount of
“wired-in” knowledge: instincts, ideals, and so on. The other theory,
that of the _tabula rasa_ or clean slate new brain, argues that each of
us organizes an essentially random net of nerves into ordered
intelligence. Both theories are being investigated with computers, and
as a result light is beginning to be shed on the workings of our brains.

[Illustration:

  _The Upjohn Company, Ezra Stoller Associates Photo_

  “A moment at a concert” is diagrammed by brain model, showing eyes,
    ears, nerves, and structures analogous to brain. Picture at top
    represents perception.
]

There is another division of philosophical thought in the mechanistic
versus _elan vital_ argument. In other words, is the entire mind to be
found in its constituent parts, or is there an intangible extra
something that really breathes life into us? Whatever the correct
concept, the brain does record impressions it can later recall. No one
yet knows just how this is done, but several theories have been
advanced. One of these describes a “chain circuit” set up in a neuron
network by messages from the body’s sensors. This circuit, once started,
continues to circle through the brain and is on tap whenever that
particular experience needs to be recalled. The term “reverberate” is
used in connection with this kind of memory, seeming to be a good
scientific basis for the poetic “echoes of the past.” Reverberation
circuits also provide the memory for some computers.

Among other explanations of memory is that of conditioning the neurons
to operate more “easily,” so that certain paths are readily traversed by
brain impulses. This could be effected by chemical changes locally, and
such a technique too is used in computers.

However the brain accomplishes its job, it is certain that it evolved in
its present form as a result of the environment its cells have had to
function in for billions of years. Its prime purpose has been one of
survival, and for this reason some argue that it is not particularly
well adapted to abstract reasoning. Although the brain can do a wide
variety of things from dreaming to picking out one single voice amid the
hubbub of noise at a social gathering—a phenomenon scientists have given
the descriptive name of “cocktail party effect”—men like Ashby consider
it a very inflexible piece of equipment not well suited to pure logic.
As a test of your brain as a logical device, consider the following
problem from the Litton Industries “Problematical Recreations.”

If Sara shouldn’t, then Wanda would. It is impossible that the
statements: “Sara should” and “Camille couldn’t” can both be true at the
same time. If Wanda could, then Sara should and Camille could. Therefore
Camille could. Is this conclusion valid?

If your head starts to swim, you are not alone. Very few humans solve
such problems easily. Interestingly, those who do, make good computer
programmers.


                         _The Computer’s Brain_

Just as we have an anthropomorphic God, many people have done their best
to endow the computer with human characteristics. Not only in fiction
but also in real life, the electronic brains have been described as
neurotic and frustrated on occasion, and also as being afraid and even
having morning sickness! A salesman for a line of computers was asked to
explain in understandable terms the difference between two computers
whose specifications confused a customer. “Let’s put it this way,” the
salesman said, “The 740 thinks the 690 is a moron!”

We can begin to investigate the question of computer intelligence by
again looking up a definition. The word “compute” means literally to
think, or reckon, with. Early computers such as counting sticks, the
abacus, and the adding machine are obviously something man thinks with.
Even though we may know the multiplication tables, we find it easier and
_safer_ to use a mechanical device to remember and even to perform
operations for us.

These homely devices do not possess sufficient “intelligence” to raise
any fears in our minds. The abacus, for example, displays only what we
might charitably call the property of memory. It has a certain number of
rows, each row with a fixed number of beads. While it is not fallible,
as is the human who uses it, it is far more limited in scope. All it can
ever do is help us to add or subtract, and if we are clever, to
multiply, divide, do square roots, and so on. If we are looking for
purposive behavior in computing machines, it is only when we get to the
adding machine that a glimmer appears. When a problem is set in and the
proper button pushed, this device is compelled to go through the
gear-whirring or whatever required to return it to a state of
equilibrium with its problem solved.

So far we might facetiously describe the difference in the goal-seeking
characteristics of man and machine by recalling that man seeks lofty
goals like climbing mountains simply because they are there, while the
computer seeks its goal much like the steel ball in the pinball machine,
impelled by gravity and the built-in springs and chutes of the device.
When we come to a more advanced computer, however, we begin to have
difficulty in assessing characteristics. For the JOHNNIAC, built by Rand
and named for John von Neumann, can prove the propositions in the
_Principia Mathematica_ of Whitehead and Russell. It can also “learn” to
play a mediocre game of chess.

If we investigate the workings of a digital computer, we find much to
remind us of the human brain. First is the obvious similarity of on-off,
yes-no operation. This implies a power source, usually electrical, and a
number of two-position switches. The over-all configuration of the
classic computer resembles, in principal if not physical appearance,
that of the human brain and its accessories.

As we have learned, the electronic computer has an input section, a
control, an arithmetic (or logic) section, a memory, and an output.
Looking into the arithmetic and memory sections, we find a number of
comparisons with the brain. The computer uses power, far more than the
brain. A single transistor, which forms only part of a neuron, may use a
tenth of a watt; the brain is ahead on this score by a factor of
millions to one.

Electronic switches have an advantage over the neuron in that they are
much faster acting. So fast have they become that engineers have had to
coin new terms like nanosecond and picosecond, for a billionth and a
trillionth of a second. Thus, the computer’s individual elements are
perhaps 100,000 times faster than those of the brain.

There is no computer in existence with the equivalent of 10 billion
neurons. One ambitious _system_ of computers does use half a million
transistors, plus many other parts, but even these relatively few would
not fit under a size 7-1/2 hat. One advanced technique, using a “2-D”
metal film circuitry immersed in liquid helium for supercooling,
hopefully will yield a packaging density of about 3-1/2 million parts
per cubic foot in comparison with the brain’s trillion-part density.

We have mentioned the computer memory that included the “delay line,”
remindful of the “chain circuit” in the brain. Electrical impulses were
converted to acoustic signals in mercury, traversed the mercury, and
were reconverted to electrical impulses. Early memory storage systems
were “serial” in nature, like those stored on a tape reel. To find one
bit of information required searching the whole reel. Now random-access
methods are being used with memory core storage systems so wired that
any one bit of information can be reached in about the same amount of
time. This magnetic core memory stores information as a magnetic field,
again analogous to a memory theory for the human brain except that the
neuron is thought to undergo a chemical rather than magnetic change.

[Illustration:

  _General Electric Co., Computer Dept._

  Tiny ferrite cores like these make up the memory of some computers.
    Each core stores one “bit” of information.
]

Until recently, computers have been primarily sequential, or serially
operating, machines. As pointed out earlier, the brain operates in
parallel and makes up for its slower operating individual parts in this
way. Designers are now working on parallel operation for computers, an
improvement that may be even more important than random-access memory.


                               _Bionics_

It is obvious that while there are many differences in the brain and the
computer there are also many striking similarities. These similarities
have given rise to the computer-age science of “bionics.” A coinage of
Major J. E. Steele of the Air Force’s Wright Air Development Center,
_bionics_ means applying knowledge of biology and biological techniques
to the design of electronic devices and systems. The Air Force and other
groups are conducting broad research programs in this field.

As an indication of the scope of bionics, Dr. Steele himself is a flight
surgeon, primarily trained as neurologist and psychiatrist, with
graduate work in electronics and mathematics. Those engaged in bionics
research include mathematicians, physical scientists, embryologists,
philosophers, neurophysiologists, psychologists, plus scientists and
engineers in the more generally thought of computer fields of
electronics and other engineering disciplines.

A recent report from M.I.T. is indicative of the type of work being
done: “What the Frog’s Eyes Tell the Frog.” A more ambitious project is
one called simply “Hand,” which is just that. Developed by Dr. Heinrich
Ernst, “Hand” is a computer-controlled mechanical hand that is described
as the first artificial device to possess a limited understanding of the
outside world. Although it will undoubtedly have industrial and other
applications, “Hand” was developed primarily as a study of the cognitive
processes of man and animals.

Besides the Air Force’s formal bionics program, there are other research
projects of somewhat similar nature. At Harvard, psychologists Bruner
and Miller direct a Center for Cognitive Studies, and among the
scientists who will contribute are computer experts. Oddly, man knows
little of his own cognitive or learning process despite the centuries of
study of the human mind. It has been said that we know more about
Pavlov’s dog and Skinner’s pigeons than we do about ourselves, but now
we are trying to find out. Some find it logical that man study the
animals or computer rather than his own mind, incidentally, since they
doubt that an intelligence can understand itself anyway.

As an example of the importance placed on this new discipline, the
University of California at Los Angeles recently originated a course in
its medical school entitled “Introduction to the Function and Structure
of the Nervous System,” designed to help bridge the gap between
engineering and biology. In Russia, M. Livanov of the Soviet Academy
Research Institute of Physiology in Higher Nervous Activity has used a
computer coupled with an electric encephaloscope in an effort to
establish the pattern of cortical connections in the brain.

While many experts argue that we should not necessarily copy the brain
in designing computers, since the brain is admittedly a survival device
and somewhat inflexible as a result of its conditioning, it looks
already as if much benefit has come from the bionics approach.

The circuitry of early computers comprised what is called “soldered”
learning. This means that the connections from certain components hook
up to certain other components, so that when switches operated in a
given order, built-in results followed. One early teaching device,
called the Electric Questionnaire, illustrates this built-in knowledge.
A card of questions and answers is slipped over pegs that are actually
terminals of interconnected wires. Probes hooked to a battery are
touched to a question and the supposed correct answer. If the circuit is
completed, a light glows; otherwise the learner tries other answers
until successful.

More sophisticated systems are those of “forced” learning and free
association. Pioneer attempts at teaching a computer to “perceive” were
conducted at Cornell University under contract with the Air Force to
investigate a random-network theory of learning formulated by Dr. Frank
Rosenblatt. Specifically, the Perceptron learns to recognize letters
placed in front of its “eyes,” an array of 400 photocells. The human
brain accomplishes perception in several steps, though at a high enough
rate of operation to be thought of as a continuous, almost
instantaneous, act. Stimuli are received by sense organs; impulses
travel to neurons and form interconnections resulting in judgment,
action if necessary, and memory. The Perceptron machine functions in
much the same manner.

[Illustration:

  _Electronics_

  Simplified version of a mammalian visual system (A) and Perceptron
    simulating the biological network (B).
]

The forced learning technique, in which Perceptron was told when it
correctly identified a letter, and when it missed, was used first. Later
it was found that “corrective” or reinforced teaching, which notes only
errors, was more effective. After Perceptron had seen each letter
fifteen times and received proper correction, it could subsequently
identify all the letters correctly.

Announcement of Perceptron triggered many wild headlines and a general
misconception in the public mind. Dr. Rosenblatt and other developers
wisely refuse to comment on the potential of his machine, but the number
of experiments being conducted indicates wide scientific interest, and
_perceptron_ has attained the prestige of an uncapitalized generic term.
However, the theory of its random process has been questioned by
scientists including Theodore Kalin, one of the builders of an early
electrical logic machine. Kalin feels that intelligence presupposes a
certain minimum of _a priori_ knowledge: the wired-in learning of the
computer or the instincts or inherited qualities of animals. This of
course echoes the thoughts of Kant who deplored the notion as similar to
all the books and papers in a library somehow arranging themselves
properly on the shelves and in filing cabinets.

Indeed, the whole idea of finding human intelligence mirrored in the
electronic innards of the computer has been flatly denounced at some
scientific symposiums. Computers given an intelligence test at the
University of Michigan “flunked,” according to researchers. Another
charge is that the reaction of the brain’s neuron depends on its history
and thus cannot be compared with the computer. However, other
researchers seem to have anticipated this weakness and are working on
electronic or electrochemical neurons that also are conditioned by their
input. Despite criticism, the bionics work proceeds on a broad front.

More recently a machine called Cybertron has been developed by the
Raytheon Company. This more sophisticated machine is being trained to
recognize sonar sounds, using the corrective technique. If Cybertron
errs, the teacher pushes a “goof” button. When the machine is fully
developed, Raytheon feels it will be able to recognize all typical
American word sounds, using its 192 learning elements, and to type them
out.

Computers generally do “logical” operations. Many human problems do not
seem to be logical, and can be solved only by experience, as the
mathematician Gödel demonstrated some years ago. Since Cybertron solves
such “alogical” problems, its builders prefer not to call it a computer,
but rather a self-organizing data-processor that adapts to its
environment. Among the variety of tasks that Cybertron could perform are
the grading of produce and the recognition of radar signals. Raytheon
foresees wide application for Cybertron as a master learner with
apprentice machines incapable of learning but able to “pick the brains”
of Cybertron and thus do similar tasks.

[Illustration:

  _Cornell Aeronautical Laboratory_

  With the letter C in its field of view, Perceptron’s photocells at top
    center are activated. Simultaneously, response units in panel at
    right identify the letter correctly.
]

The assembly of machines like Perceptron and Cybertron requires elements
that simulate the brain’s neuron. One such component which has evolved
from bionics research is the Artron, or artificial neuron. Inside the
Artron are logic gates and inhibit gates. By means of reward or
punishment, the Artron learns to operate a “statistical switch” and send
impulses to other Artrons or to a readout. There are two interesting
parallels here besides the operation of a simulated neural net. One is
the statistical approach to decisions and learning. The late John von
Neumann theorized that the brain’s actions might be statistical, or
based on probability. Second, the designers of Artron see a similarity
in its operation and Darwin’s theory of natural selection.

Another new component in the bionics approach is the “neuristor.” This
semiconductor diode simulates the axon, the nerve fiber that connects
with the neuron. Another device is the “memistor,” unique in that it
uses electrochemical phenomena to function as a memory unit. A different
kind of artificial neuron called MIND is made up of magnetic cores.

There is another plus factor in this duplication of what we think is the
system used by the brain. While one neuron may not be as reliable as a
vacuum tube or transistor, the complete brain is millions of times more
dependable than any of its single parts. This happy end result is just
the reverse of what man has come up with in his complex computer
systems. For instance, individual parts in the Minuteman missile must
have a reliability factor of 99.9993% so that the system will have a
fair chance of working properly. Duplication of the brain’s network may
well lead to electronic systems that are many times more reliable than
any of their individual parts.

Bionics is apparently a fruitful approach, both for benefiting computer
technology and for learning more about the human brain. As an example,
consider the fact that work with the Perceptron indicated that
punishment was more effective in the learning process than punishment
and reward together. This of course does not say that such a method
would work best with a human subject, but if separate tests with human
beings proved a similar result, it might then be safe to infer some
similarity between the human and computer brain.

One of the biggest roadblocks to implementation of a humanlike neural
net is economic. Since there are some 10 billion neurons in the brain,
and early electronic neurons consisted of several components including
transistors which are a bargain at $2 each, building such a computer
might double our national debt. Bionics workers have been thinking
dreamily in terms of something like one cent per artificial neuron. This
is a ridiculously low figure, but even at that a one-tenth brainpower
computer with only a billion penny neurons would cost $10 million for
those components alone!

[Illustration:

  _Cornell Aeronautical Laboratory_

  Random wiring network between the Mark I Perceptron’s 400 photocell
    sensors and the machine’s association units.... The Mark I has ten
    sensory output connections to each of its 512 association units.
]

Not yet whipped, researchers are now thinking in terms of mass-producing
lattices of thin metal, in effect many thousands of elements in a
microscopic space, and propagating electrochemical waves rather than an
electrical current through them.

[Illustration:

  _Raytheon Co._

  When Cybertron doesn’t catch on to a new lesson, engineers push the
    goof button to punish the machine. When it learns correctly it is
    allowed to continue its studies with no interruption, thus it
    constantly improves its skill.
]

Other ideas include getting down to the molecular level for components.
If this is achieved it will be a downhill pull, for even the human
neuron consists of many molecules. Farfetched as these ideas seem,
packaging densities of 100 billion per cubic foot are being talked of as
foreseeable in less than ten years. This is only about ten times as
bulky as the goal, the human brain, and when it is achieved the computer
will be entitled to a big head.


                      _The Computer as a Thinker_

About the time Johnny was having all his trouble reading, a computer
named JOHNNIAC was given the basic theorems needed, and then asked to
prove the propositional calculus in the _Principia Mathematica_, a task
certainly over the heads of most of us. The computer waded through the
job with no particular strain, and even turned in one proof more elegant
than human brains had found before. When the same problems were given to
an engineer unfamiliar with that branch of mathematics, his verbalized
problem-solving technique paralleled that of JOHNNIAC. Asked if he had
been thinking, the engineer said he “surely thought so!”

In his interesting department in _Scientific American_, mathematical
gamester Martin Gardner describes a simple set of punched cards for
solving the type of logic problem discussed earlier in this chapter.
Using these cards and a simple digital type of manipulation, we happily
learn that Camille surely could. The problem is a simple, three-premise
type in two-valued logic and can be solved by any self-respecting
digital computer in a split second. A few demonstrations like this give
a rather disconcerting insight into our brain’s limitations and build
more respect for the computer’s intelligence.

When we hear of expensive computers apparently frittering away their
valuable time playing games we may well wonder how come. But games, it
turns out, are an ideal testing ground for problem-solving ability and
hence intelligence. Back in 1957, computer experts Simon and Newell
predicted that in ten years the chess champion of the world would be a
computer. Master players most likely laughed up their sleeves, and thus
far the electronic machine has done no better than play a routine game
against a human amateur. This, of course, is not a mean achievement.
Wise heads are supposed to have responded to the prediction with “So
what?”

[Illustration:

  Photo at left from _Organization of the Cerebral Cortex_, by D. A
    Sholl, J. Wiley and Sons. Right, _General Electric Research
    Laboratory_

  Photo at right shows a “crossed-film cryotron” shift register—an
    advanced computer element. The separation of active crossovers shown
    is comparable to the separation of nerve cells in the section of cat
    brain shown at left.
]

Alex Bernstein of IBM worked out a program for the 704 computer in which
the machine looks ahead four moves before each of its plays. Even this
limited look ahead requires 2,800 calculations, and the 704 takes eight
minutes deliberating. Occasionally it makes a move the experts rate as
masterful.

Chess is a far more complex game even than it appears to those of us on
the sidelines. In an average game there are forty moves and each has
about thirty possibilities. So far this sounds innocuous, but
mathematics shows that there are thus 10^{120} possible moves in any one
game. This number is a 1 followed by 120 zeros, and to underline its
size it has been estimated that even if a million games a second were
played, the possibilities would not be exhausted in our lifetime!

Obviously human chess wizards do not investigate all possible moves.
Instead they use heuristic reasoning, or hunch playing, to cut corners.
The JOHNNIAC computer is investigating such approaches to
computer-playing chess, in a movement away from rigorously programmed
routines or “algorithms.” Algorithms are formulas or equations such as
the quadratic equation used in finding roots. If indeed the computer
does dethrone the human chess champ by 1967, it will be exceedingly hard
to argue that the machine is not thinking.

The word “heuristic” comes from the Greek _heuriskein_, meaning to
discover or invent. An example of what it is and how important it is can
be seen in the recent disproving of a famous conjecture made by the
mathematician Euler some 180 years ago. Euler was interested in the
properties of so-called “magic squares” in which letters are arranged
vertically and horizontally. While it is possible to arrange the letters
_a_, _b_, _c_, _d_, and _e_ in such a square so that all are present in
each row and in different order, Euler didn’t think such was the case
with a square having six units on a side. He tried it, visualizing
officers of different rank arranged in rows. Convinced that it would not
work, he extended his educated guess to squares having units of ten,
fourteen, and other even numbers not divisible by four. He didn’t
actually prove his conjecture, because the amount of paperwork makes it
practically impossible.

In 1901 a mathematician did try all the possible configurations of the
square of six units and found that Euler was indeed correct. It was
assumed that ten was impossible too, until 1958 when three American
mathematicians spoiled Euler’s theory by finding workable magic squares
having ten units per side. They did not do this by exhausting all the
possibilities, for such a chore would have been humanly impossible. In
fact, a computer labored for 100 hours and completed only a tiny
fraction of the job. The square-seekers concluded that it would take
even the high-speed computer upwards of a century to do the job, so
instead they used hunches or inspired guesses, working out a heuristic
for the task. The point of importance is that not only man, but the
computer as well, despite its fantastic speed, must learn to use
heuristic reasoning rather than blindly plowing through all possible
solutions. There are just too many numbers!

Computers play other games too, from tick-tack-toe and Nim, which it
plays flawlessly, to Go and checkers. Dr. Arthur Samuel of IBM has
taught the 704 computer to play checkers well enough to beat him
regularly, though Dr. Samuel, scientist that he is, admits he is not a
great checker-player. He has used two types of learning in the program:
“rote” and “generalization.” So far these have been used separately,
while human players use both types of learning in a game.

American scientists visiting Russia recently reported that the Russians,
like some of us, were amazed to hear that computer time was allotted to
the mere playing of games. The real goal in all this game-playing is to
learn how to do other more important things. Gaming is being applied to
war strategy and to business management. Corporation executives are
playing games with computers that simulate the operation of their firms,
both to improve methods and to learn about themselves and their
employees. A General Problem-Solver computer is being developed too; one
which can solve problems like the cannibals and the missionaries and
then do mathematical equations and other types of thinking. As was
pointed out, when the computer’s method of solving a problem is compared
with the protocol used by a person (by having him think aloud as he goes
through the problem) it is seen that both use pretty much the same
tricks and short cuts.

As the computer keeps closing the gap, we can push the goal back by
redefining our terms. This is much like dangling a carrot on a stick,
and with the computer doggedly taking the part of the donkey, it is a
pretty good technological flail. By making the true test of intelligence
something like artistic creativity, we can rule out the machine unless
it can write poetry, compose music, or paint a picture. So far the
computer has done the first two, and the last poses no particular
problem, though debugging the machine might be a messy operation. True,
the machine’s poetry is only about beatnik level:


                                CHILDREN

           Sob suddenly, the bongos are moving.
           Or could we find that tall child?
           And dividing honestly was like praying badly,
           And while the boy is obese, all blast could climb.
           First you become oblong,
           To weep is unctious, to move is poor.

This masterpiece, produced by a computer in the Librascope Laboratory
for Automata Research, is not as obscure as an Eliot or a Nostradamus.
Computer music has not yet brought audiences to their feet in Carnegie
Hall. The machine’s detractors may well claim that it has produced
nothing truly great; nothing worthy of an Einstein or Keats or Vermeer.
But then, how many of us people have?

There is yet another way we can ban the computer from membership in our
human society. While human beings occasionally think they are machines,
and Dr. Bruno Bettelheim has documented a case history of “Joey” who was
so convinced that he was a machine that he had to keep himself plugged
in to stay alive, no machine has yet demonstrated that it is consciously
aware of itself, as human beings are.

Machines are, hopefully, objective. Consciousness seems to be subjective
in the extreme; indeed, some feel that it is a thing one of us cannot
hope to convey as intelligence to another and thus has no scientific
importance. It is also noted that the thinking and learning processes
can be carried out with no need for consciousness of what we are doing.
An example given is that of the cyclist who learns, without being
“aware” of the fact, that to turn his machine left he must first make a
slight swing to the right in order to keep from falling outward during
his left turn. This observation in itself is not final proof of the
pudding, of course, unless we are aiming only to make a mechanical
bike-rider, but many of our other actions are carried out more or less
mechanically without calling attention to themselves. Just as certainly,
however, the thing called consciousness plays a vital role in human
thinking. Perhaps the machine must learn to do this before it can be
truly creative.

Although we have described some fairly “exotic” devices, it should be
remembered that the computers in use outside of the laboratory today are
fairly old-fashioned second-generation models. They have progressed from
vacuum tubes or mechanical relays to “solid-state” components. When
Artrons and neuristors and memistors and other more sophisticated parts
are standard, we can look for a vast increase in the brain power of
computers.

The Gilfillan radar ground-controlled-approach system for aircraft that
“sees” the plane on the radar scope, computes the proper path for it to
follow, and then selects the right voice commands from a stored-tape
memory seems to be thinking and acting already. The addition of eyes and
ears plus limbs and locomotion to the computer, foreseen now in the
photocell eyes of Perceptron, the ears of Cybertron, and dexterity of
Mobot and Hand, will move the computer from mere brain to robot.

Some people profess to worry about what will happen when the computer
itself realizes that it is thinking, calling to mind the apocryphal
story of the machine that was asked if there was a God. After brief
cogitation, it said, “_Now_ there is.” To offset such a chilling
possibility, it is comforting to recall the post-office electronic brain
that mistook the Christmas seals on packages for foreign stamps, and the
Army computer that ordered millions of dollars worth of supplies that
weren’t needed. Or perhaps it isn’t comforting, at that!

The question of whether or not a computer actually thinks is still a
controversy, though not as much so as it was a few years ago. The
computer looks and acts as if it is thinking, but the true scientist
prefers to reserve judgment in the spirit of one shown a black sheep
some distance away. “_This_ side is black,” he admitted, “but let’s
investigate further.”


------------------------------------------------------------------------


    “_For forms of government let fools contest,
    That which is best administered is best._”

                    —Pope




                        7: Uncle Sam’s Computers


The modern electronic version of the computer is about fifteen years
old, and like most teen-agers, it is a precocious child. To list all the
applications in which it has made a place for itself would take several
pages and an inclusive listing from Airlines to Zoology. There are
hundreds of different types, priced from less than one hundred dollars
to more than ten millions. The latter are so expensive that outright
purchase is not usually possible for users. Rental or leasing
arrangements are therefore available; and there are a growing number of
computer centers to which the customer can take or send his work and
have it done. There are also do-it-yourself computer facilities, much
like those for laundry, dry cleaning, and so forth, as well as
installations in trailers that move from place to place. Most require a
source of conventional electric power, but there are some portable
models that operate on batteries.

Scanning the list of jobs the computer now does, it would seem
impossible to classify the varied tasks. Since many machines are
versatile, general-purpose types, it is even more difficult to
definitely categorize the computer. Dr. John R. Pierce, an expert at the
Bell Telephone Laboratories, describes some of the chores done by a
digital computer in a typical session at Bell:

Check parts of a computer program used in connection with machine
methods for processing manufacturing information.

Process and analyze data on telephone transmission which have been
transmitted to the laboratories by teletypewriter and automatically
punched on cards for computer processing.

Solve a partial differential equation.

Compute details of the earth’s magnetic field.

Check part of a program used to handle programming cards.

Fit curves to data by translating numerical information into graphs.

Locate an error in a program designed to process psychological data.

These “simple” problems required but three minutes of the computer’s
time. A larger task, something like solving 350 mathematical logic
theorems from _Principia Mathematica_, takes a bit longer—eight and a
half minutes, to be exact.

Despite this versatility, it is generally possible to break the
computer’s capabilities down into broad classifications. First we can
say that it does either simple data-processing, or scientific
computations. Each of these can then be further subdivided ad infinitum.
Examples will be seen as we describe uses of computers on the following
pages. Since the government was the first user of computers, beginning
back in 1890 with Hollerith’s punched-card machines, we would do well to
see what other work it has put the computer to in the years that have
elapsed.


                      _The Computer in Washington_

An inventory of electronic computers installed in the Federal Government
by the end of 1961 totaled 800, with 200 more on order. These figures
are exclusive of those for tactical and classified use by the Department
of Defense. Some 45,000 people are engaged in computer operations in the
government, and a total expenditure of about $1.5 billion is estimated.
An indication of the importance accorded the computer by Washington is
the Interagency Data Processing Committee, concerned with questions of
sharing of computers in geographic areas, setting up of a “library” of
applications, and assurance of continued computer operation in the event
of attack or other emergency. Users of computers, in addition to the
Department of Defense, are the Atomic Energy Commission, Department of
Commerce, National Aeronautics and Space Agency, Federal Aviation
Agency, Post Office Department, and others for a total of 43 agencies.
The Peace Corps, for example, recently announced that it would acquire a
computer for use in its work.

Red tape is not the only output from Washington, D.C. Not long ago the
Hoover Commission estimated that our Federal Government also produces 25
_billion_ pieces of paper each year! Someone else converted this already
impressive statistic into the more startling information that placed end
to end these papers would reach the moon four times—in triplicate, of
course! Data-processing, then, the handling of information, would seem
to be the major part of the computer’s work for Uncle Sam.

The Census Bureau was the first government user of the computer, and it
continues to handle its work in this way. In 1951 the government
procured a UNIVAC I to take over this onerous chore from its
predecessors. Beginning with the 1950 census, the computer has been in
operation practically twenty-four hours a day, seven days a week. In its
first ten years it performed more than 510 billion mathematical
operations in keeping pace with our exploding population. We are
producing more than paperwork, it seems. The 1950 census required four
years to process. With newer computers the 1960 count will take only
half as long despite the population explosion.

Information-handling computers make possible another important phase of
the government’s work. In 1936, machines began to process Social
Security records, which are becoming a monumental pile of paperwork
themselves with close to 100 million accounts that must be kept up to
date. Social Security numbers recently turned up in government computers
handling another job—that of income-tax bookkeeping.

The U.S. Commissioner of Internal Revenue, Mortimer Caplin, put a pilot
system of computer accounting of tax records into operation in January
of 1962 in the Atlanta region. In 1963, the Philadelphia Center will
follow suit, and by 1966 all income-tax accounting will whiz through
tape reels into computers. The figures on tax greenbacks laid end to end
are not available, but it is known that 400 miles of magnetic tape will
be needed to hold all the records.

The new system will make it tough on the income-tax chiseler. Caplin
points out that not only the withholding-tax information from the
employer, and forms from the employee, but also dividend statements and
other supplementary income information will funnel automatically into
John Doe’s portion of the tape. If John is moonlighting, holding down a
second job he might forget to mention, the computer will spot it and
charge a tax on it. The apprehended tax-dodger may well call the
computer an infernal revenue machine.

There are of course many other ways the computer is helping out in the
complex problems of government, both Federal and local. The computer has
already figured in national elections, making predictions well in
advance as to the outcome. Now the machines are being used in the actual
voting procedure. In 1952 an IBM computer predicted Eisenhower’s victory
within two hours after the first polls closed. In the early days of
computer predictions, the men using them were overly cautious and afraid
to accept the machine’s word. Techniques and confidence have improved
with practice, and in 1960 IBM’s RAMAC predicted victory for Kennedy at
8:12 P.M. election night.

To make accurate predictions, the computer is given information from
preceding elections. In 1960 it was fed the results of the 1956, 1952,
1948, and 1928 (because of the religious considerations) elections.
Forecasters were able to ask the computer such questions as, “How is
Nixon doing compared with Eisenhower’s showing in 1952?” “How is Kennedy
doing compared with Al Smith back in 1928?” “Is labor voting as a bloc?”
and “How solid is the South?” The computer is now an accepted part of
network equipment for election reporting. ABC used the Remington Rand
UNIVAC; CBS, IBM RAMAC and other machines; and NBC the RCA 501.

[Illustration:

  _International Business Machines Corp._

  Computers are used to predict the results of elections.
]

In addition to forecasting results, computers are beginning to do other
election work. Los Angeles County experimented with a computer method of
counting votes in 1960. Greene County, Ohio, used punched cards for
ballots for 50,000 voters in a pioneering computer voting system. The
cards were processed in a UNIVAC computer at Dayton Air Force Depot. A
bolder suggestion is that of political scientist R. M. Goldman of
Michigan State University: actual voting by telephone-operated computer!

To solve another problem area in voting, the use of computers was
recently proposed at a state congressional hearing in Boston.
Redistricting, the bugaboo that led to “gerrymandering,” might well be
done by “unbiased” computers which would arrive at an optimum
redistricting plan. These unbiased results would be “beyond politics and
in the best interests of the voters and the State,” according to the
computer expert who proposed the plan.

Moving from voting to a more complicated problem, that of urban renewal,
the University of Washington is conducting a survey under federal grant
on the extent of deterioration and the causes of decay in Spokane
residential, commercial, and industrial areas. The IBM 709 computer
makes possible an accurate and extensive survey expected to shed light
on areas of arrested development, and on the amount of tax revenue lost
because of existing blight.


                        _Electronic Legal Eagle_

Some writers see the clearest evidence of the victory of the computer—if
indeed we admit to there ever having been any real battle—in the
admission by the legal profession that it must begin to chart the legal
seas of the computer age.

In 1961 the American Law Institute and the American Bar Association,
feeling that the computer will cast its “automated shadow on every phase
of society,” conducted a joint three-day seminar in Washington, D.C.
Titled “Legal Problems in the Use of Electronic Data Processing in
Business, Industry and Law,” the seminar discussed “function and
operation of computers and their impact on tort, tax, corporation,
labor, contract, banking, sales, antitrust, patent and copyright law, as
well as on the law of evidence and trial practice.”

Lawyer Roy Freed of the Philadelphia Bar, in a booklet called “A
Lawyer’s Guide Through the Computer Maze,” describes the working of the
machine and then poses some challenging legal questions.

What duty does the company acting as a computer service organization
have to preserve the confidential nature of the data it processes for
its customers?

Can business records placed on magnetic tape be used in evidence, or
must the original records be preserved?

How long can corporate management lag behind others in their industry in
adopting machine data-processing systems before they expose themselves
to a mismanagement charge?

To what extent should the manufacturer of a complex product that has a
potential for causing harm try to minimize his liability as a maker by
anticipating design defects through simulated operation on the computer?

Other legal experts asked other questions. If an electronically
processed check is bounced erroneously, who is responsible? If a
noncomputerized railroad has a train wreck, can the road be sued on the
premise that the accident would not have occurred with modern traffic
controls? Or if the reverse occurs, can an anticomputer claimant win a
suit against the machine?

Applications of the computer in patent law may lead to more thorough
search in addition to higher speed. This could well clear another
bottleneck by issuing fewer and faster patents. But copyright violation
problems lie in the possibility of making copies of tapes or other media
suitable for the computer’s use. The altering or falsification of
computer data also poses a tricky legal problem; there is already a
precedent in the Wall Street man who juggled the punched cards on the
computer to his own advantage.

Perhaps there was one question none of the lawyers present had the
courage to bring up: what if the day comes when the court itself is a
computer, and the case is presented to it as a stack of cards, or a
prepunched or magnetized tape? Such a mechanized justice was fancifully
depicted on a television thriller by Ray Bradbury.


                          _Computers in Khaki_

Despite the low IQ it has been accused of, it was inevitable that the
computer be drafted. In the 40’s we were desperate. Included in
government use of computers are military research, development, and
tactical and strategic methods. World War II was a different kind of
war, a complicated, electronic war that required advanced methods of
operation. At Eastertime in 1942, IBM answered an urgent call from
Washington and gathered all available data-processing machines for use
by the military. Punched cards kept track of allotments, insurance, and
the logistics of running a war. Mobile computing machines operated close
to the front lines, and were important enough that a captured German
officer was carrying urgent orders to bring in one of these units.

[Illustration:

  _Motorola, Inc., Military Electronics Division_

  Technician checks circuitry of airborne digital computer.
]

Besides the mundane effort of mere data-processing, wartime computers
did important cloak-and-dagger work as well. A report came in from
Allied intelligence that the Germans were working on a frightening new
development—an electrically powered cannon. If it were successful we
would need some kind of counterweapon. But the dike was leaking in a
hundred other places too, and there was not time or equipment to do
everything it seemed we might have to do. The answer was to feed some
complex mathematics to an IBM computer called the Automatic Sequence
Controlled Calculator—mathematics describing the new cannon. The
computer cogitated briefly and decided that the Germans were on the
wrong track; that the gun would not work. We therefore ignored the
threat, letting the Germans waste their valuable time going down the
blind alley, and turned our efforts elsewhere.

We have said that World War II was a different kind of war. One new
development to bear out this difference was called “Operations
Research”—the reduction of any program to mathematical formulas and the
investigation of these formulas rather than a conventional, intuitive
approach. The technique was pioneered in England, spread to the United
States, and is now one of the most powerful tools not only of the
military but also of government and business. The computer has made
operations research a more powerful technique by permitting the analysis
of thousands or millions of possibilities in hours instead of lifetimes.

Back in the days of bows and arrows, the soldier had no need for a
computer. Even the rifleman required little more than a simple sight and
maybe a bit of Kentucky windage. With the coming of long-range
artillery, computers became desirable, and now we have moved into an age
of warfare that would be impossible without high-speed computing
machines.

In 1948 IBM introduced a computer known as SSEC for Selective Sequence
Electronic Calculator. This machine was put to work on a problem for the
Los Alamos Atomic Energy Laboratory, a problem called “Hippo.” Hippo was
as unwieldy as its name, requiring some nine million involved
mathematical operations that would have taken about 1,500 man-years of
skilled time. That many mathematicians or that much time was not
available, of course, and SSEC clicked through the job in 150 hours by
itself. Another computer, the MANIAC, designed by John von Neumann, is
credited with beating the Russians to the punch with the hydrogen bomb.

As an outgrowth of operations research, the simulation of war games has
become an important part of military work. A number of firms, including
System Development Corporation, Technical Operations, Inc., and others,
devote much of their time to “playing games” to work out the optimum
strategy and tactics for war in case we find it necessary again.

It is perhaps not paradoxical that war be considered a game. As William
Cowper said, “War’s a game, which were their subjects wise, Kings would
not play at.” The game of chess, conversely, stems from war and its
tactics. Indeed, the term checkmate, for victory, comes from the Persian
words _shah mat_, the king is dead.

Through the years many war games have been developed, games which
eliminate the physical conflict but preserve the intellectual
maneuvering necessary for waging “war.” John von Neumann was one of the
more recent to turn his great genius to this subject in the development
of his “minimax” theory. This is an outline of a situation in which
consequences of decisions depend on the actions of an opponent. We have
seen that the computer, though not yet world champion, can play chess;
the minimax theory is more grist for its electronic mill.

Tech-ops operates the Combat Operations Research Group for the U.S.
Continental Army Command at Fort Monroe, Virginia. Among the games
played here with computers are SYNTAC, in which field-experienced
officers evaluate new weapons and tactics, and AUTOTAG, a computer
simulation of tank-antitank combat. Other projects of this firm include
air battle simulations, ship loading and other logistics problems,
fallout studies, and defense against missile attacks. The beauty of such
schemes is that we will not make the mistake of the Germans with their
electric cannon. When the computer blinks “Tilt” or an equivalent, the
engineers may have red faces, but no huge amount of time or money will
have been spent before they sigh, “Back to the old drawing board!”

[Illustration:

  _Aeronutronic Division, Ford Motor Co._

  ARTOC (Army Tactical Operations Central) uses computer techniques for
    battlefield display and communications to aid field commanders.
]

At Picatinny Arsenal, computers evaluate ammunition by simulating as
many as a thousand battles per item. Design and management studies for
projects like Nike-Zeus and Davy Crockett are also conducted at
Picatinny. A mobile computer, called MOBIDIC, is designed for field
combat use and has been moved in three 30-foot trailers to location with
the Seventh Army in Europe. There it handles requisitions for rockets,
guided missiles, electronic equipment, and other items. MOBIDIC is just
part of the Army’s FIELDATA family of computers that includes
helicopter-transported equipment to provide field commanders with fast
and accurate data on which to base their risk decisions. Another concept
is ARTOC, for Army Tactical Operations Central, an inflatable command
post in which computers receive and process information for display on
large screens. This is a project of Aeronutronic.

In 1961 an IBM 7090 computer was installed at Ispra, Italy, for use by
the European Atomic Energy Commission (EURATOM). The computer would have
as its duties the cataloging of technical information on atomic energy,
the translation of technical publications, and use in basic research on
solutions of Boltzmann equations and other advanced physics used in
atomic work. In this country, the National Science Foundation has
acknowledged the importance of the computer in scientific investigation
by underwriting costs for such equipment for research centers in need of
them.

[Illustration:

  _International Business Machines Corp._

  Command post of SAGE, the most complex computer application to date.
]


                              _In the Air_

Beyond the realm of war gaming, the computer also forms the heart of the
hardware that such simulation and studies develop. SAGE is an example of
this, a complex warning system that protects our country from attack.
The acronym SAGE is a more dignified and impressive name than the words
it stands for—Semi-Automatic Ground Environment, an environment that by
1965 will have cost $61 billion!

Sage is not a single installation, but a vast complex of centers feeding
information from Ballistic Missile Early Warning Site radar and airborne
radar, from ships, Texas towers, and ground-based radar, and from
weather stations into a central control. This control sends the proper
signals to defensive rockets, missiles, and aircraft for action against
an invader. It does this with one hand, while with the other it keeps
tabs on normal military and commercial air traffic.

The System Development Corporation designed and IBM built the SAGE
computer, a computer already old-fashioned since it uses vacuum tubes
instead of the newer transistor devices. Despite this shortcoming, it
does a fantastic job of tracking all the aircraft and missiles in its
ken, labeling them for speed, heading, altitude, as well as the vital
information of friend or foe, and continuously plans a defense. Since it
can monitor civilian traffic as well, SAGE may one day take over control
of that too. Thus the money spent will yield a bonus in addition to the
protection SAGE has already afforded in its military role.

The Air Force uses airborne computers by the thousands. Indeed, the need
for small lightweight computers for applications in aircraft led to
early work in the miniaturization of components that made possible tiny
computers for missile and space use. Small digital computers were built
for “drone” aircraft navigation; now more advanced computers provide
“air data,” air-speed, altitude, flight attitude, pressure, and other
information.

Other Air Force computers, used in BMEWS radar, take the place of human
observers. These smart computers can recognize radar tracks that are
potential missile trajectories, discriminate among these tracks to
select hostile trajectories, and project them to impact points and
times. Called MIPS, for Missile Impact Predictor Set, the computer takes
over from its human forerunner who just can’t seem to perform the
200,000 operations a second required to do the job.

Another space-tracking computer called SPADATS has been installed at
NORAD Combat Operations Center at Colorado Springs. This computer has
the assignment of around-the-clock cataloging of all man-made objects in
space, a sizable and growing task. At Vandenberg Air Force Base, the Air
Force maintains an EDP, or Electronic Data Processing project with a
more earth-bound job of cataloging. Started back in 1957, this project
has as its primary task the efficient allocation of manpower for the
global Strategic Air Command team.

At nearby Edwards Air Force Base, an IBM 7090 computer is helping to
develop the Dyna-Soar manned space glider. This computer is also doing
work for the X-15 program, and research on fuels, lunar probes, rocket
nozzles, and nose cones. At Tinker Air Force Base in Oklahoma, a new
system of keeping track of jet engine parts, so that they go back on the
proper engine, uses a recorder “gun” wired to a central control
computer. Engine parts are metal tagged with coded letters which the
recorder “reads” and transmits to the computer for filing.

Computers play a big part in the “largest and most sophisticated
logistic data and message communications system in the world.” Delivered
to the Air Force in January of 1962, “Comlognet” connects 450 different
air bases and other installations. This system started out modestly,
handling about 10 million punched cards a day, and is heralded as only a
forerunner of an automatic system which will some day take care of the
complete interflow of data among widely separated military and civilian
locations.

Besides being part of complex navigation and bombing systems, computers
help the Air Force to score the results of practice bombing missions.
Computers control the launching of Sidewinder missiles from aircraft and
also permit accurate “toss-bombing” of nuclear payloads from fighter
bombers. These computers do all the mathematics and let the pilot
approach his target from any direction, at any speed and altitude. The
new Skybolt ballistic missile, launched from the B-52 bomber, has its
own guidance computer, which is actually a digital differential
analyzer, a hybrid device like that described in an earlier chapter. One
of the largest single computers in the Air Force is that called Finder.
Using 70,000 transistors, it does analytical work on electronic
countermeasures.

Today there are some 110,000 aircraft flying the skies in this country,
about double the number ten years ago. Not only the quantity but also
the speed of aircraft has increased, and the job of the aircraft
controller has become a nightmare. With the lives of air travelers in
his hands, this overworked FAA employee has until recently used the same
equipment that served in the days of 180 miles-per-hour piston-engine
transports.

We have discussed some examples of the computer as a director of air
traffic; the automatic ground-controlled-approach system that lands
planes in bad weather without human help is one, the mighty SAGE defense
system is another. SAGE may one day take over commercial air traffic: in
the meantime, the Federal Aviation Agency relies heavily on smaller
computers in locations all over the country.

Originally, general-purpose business computers were put to work
processing the vast quantities of data needed to keep traffic flowing
along the airways. New, special designs, including those of the
Librascope Division of General Precision, Inc., are being added as they
become available. Remington Rand UNIVAC is also working on the problem,
and UNIVAC equipment has been tested on Strategic Air Command
round-robin flights. It has posted as many as eighty in-flight Axes for
one mission, a feat that the unaided human controller can only gasp at.

Obviously, control of aircraft cannot be turned over pell-mell from
human to computer. The FAA is proceeding cautiously, and a recent report
from an industry fact-finding board recommended a “Project Beacon”
approach which will continue to rely heavily on radar plus human
controllers. But when the problems of communication between man and
machine are worked out, no human being can keep track of so many
aircraft so accurately, or compute alterations in course to prevent
collision and ensure an optimum use of air space as can the computer.

------------------------------------------------------------------------


                              _On the Sea_

The Navy uses computers too. At the David Taylor Test Basin in Maryland,
a UNIVAC LARC is busy doing design work on ship hulls. Other computers
mounted in completed Navy vessels perform navigation and gun-ranging
functions. At New London, Connecticut, a Minneapolis-Honeywell computer
simulates full scale naval battles. Radar and sonar screens in mock
submarine command posts show the maneuvering of many ships in realistic
simulations. Polaris submarines depend on special computers to launch
their missiles, and the missiles themselves mount tiny computers that
navigate Polaris to its target. Another computer task was the “sea
testing” of the nuclear submarine “Sea Wolf” before it was launched!

[Illustration:

  Photo courtesy of _Litton Systems, Inc._

  Airborne computer-indicator system in Hawkeye naval aircraft. This
    equipment performs task of surveillance, tracking, command and
    control.
]

Computers are being used by the Navy in a project that has tremendous
applications not only for military application but for civilian use as
well. Mark Twain to the contrary, a lot of people have tried to do
something about the weather, among them an Englishman named Richardson.
Back in 1922 he came up with the idea of predicting the weather for a
good-sized chunk of England. Basically his ambitious scheme was sound.
Drawing on weather stations for the data, he determined to produce a
24-hour forecast.

Unfortunately for Mr. Richardson, the English, and the world in general,
the mathematics required was so complicated that he labored for three
months on that first prediction. By then it had lost much of its
value—and it was also wrong! The only solution that Richardson could
think of was to enlist the aid of about 60,000 helpers who would be
packed into a huge stadium. Each of these people would be given data
upon which to perform some mathematical operation, and then pass on to
the next person in line. Pages would transfer results from one section
of the stadium to another, and a “conductor,” armed with a megaphone
undoubtedly along with his baton, would “direct” the weather symphony,
or perhaps cacaphony. As he lifted his baton, the helpers were to
calculate like crazy, when he lowered it they would pass the result
along. What Richardson had invented, of course, was the first
large-scale computer, a serial computer with human components. For a
number of reasons, this colossal machine was never completed. It was
obviously much easier to simply damn the weatherman.

Actually, Richardson had stumbled onto something big. He had brought
into being the idea of “numerical weather prediction.” It is known that
weather is caused by the movement of air and variations in its pressure.
Basically it is simple, knowing pressure conditions yesterday and today,
to project a line or extrapolate the conditions for tomorrow. If we know
the conditions tomorrow, we can then predict or forecast the
temperature, precipitation, and winds.

[Illustration:

  _U.S. Navy_

  Weather map prepared and printed out by computer gives data in
    graphical form. Enlarged view of weather “picture” (above) shows how
    it is formed by printed digits representing the pressure at
    reporting stations.
]

There was even the mathematics to make this possible in Richardson’s
day: the so-called “primitive equations” of the pioneer mathematician
Euler. These are six partial differential equations involving velocity,
pressure, density, temperature, and so on. But though the principle is
simple, the practical application is hopelessly involved—unless you have
a stadium filled with 60,000 willing mathematicians or a fast computer
of some other type.

In 1950 the stage was finally set for the implementation of numerical
weather prediction. First, electronic computers were available. Second,
and importantly, mathematician C. G. Rossby had worked some magic with
the original primitive equations and reduced them to a single neat
equation with only four terms. The new tool is called the Rossby
equation. Meteorologists and mathematicians at Princeton’s Institute for
Advanced Study decided to combine the Rossby equation, the MANIAC
computer, and some money available from the Office of Naval Research.
The result was JNWPU, Joint Numerical Weather Prediction Unit, later to
become NANWEP, for Navy Numerical Weather Problems Group. It is too bad
that pioneer Richardson did not live to see the exploitation of his
dream.

What NANWEP does is to take the meteorological data from some 3,000
reporting stations, compare them with those existing yesterday, and
print out a weather map for the Northern Hemisphere for tomorrow.
Because there are so many more stations reporting than the handful that
Richardson used, the number of computations has risen to the
astronomical total of about 300,000,000. Despite this, a Control Data
Corporation 1604 digital computer does the job in a good bit less time
than the three months it took Richardson. NANWEP prints out its weather
maps 40 minutes from the time all data are in.

Teletype reports come in from the thousands of weather stations; these
are punched on tape and fed to the 1604. Since the information includes
geographical position in addition to meteorological data, the computer
prints out numbers that form a map of weather coming up. Although the
meteorologist adds some clarifying lines by connecting points of equal
pressure, the “raw” map with its distinctive shaded areas is meaningful
even to the layman.

Further refinements are in the offing. As many as 10,000 weather
stations may eventually report to the central computer, which may also
learn to accept the teletype information directly with no need for the
intermediate step of punching a tape. Although it will be a long time
before a positive forecast, exact in every detail, is possible, NANWEP
already has lifted weather prediction from the educated guesswork of the
older meteorologists to truly scientific forecasting.

It turns out that numerical weather prediction brings with it some
bonuses. NANWEP can predict the action of ocean waves three days in
advance, in addition to its regular wind, temperature, and precipitation
information. So it is now being put to work preparing optimum routes for
ships. Here’s the way it would work. A ship sailing from California to
Japan requests the best routes for the voyage. Initially the computer is
given the ship’s characteristics and told how it will perform in various
sea conditions. It then integrates this information with the predicted
sea conditions for the first day’s leg, and plots several different
courses. Distances the ship would travel on each of these courses are
plotted, and a curve is drawn to connect them. Now the computer repeats
the process for the next day, so that each of the tentative courses
branches out with its own alternates. The process is repeated for each
of the five days of the voyage. Then the computer works backward,
picking the best route for the entire voyage, and gives the course to be
followed for optimum time. If that isn’t sufficiently informative for
the captain, he can request and receive not one but three courses: one
for the fastest trip regardless of sea condition, another for the
fastest trip with waves of only a certain height, and finally a course
for the fastest trip through calm water! The advantages of such a
service are immediately obvious and give a hint at many other
applications of the technique to air travel, truck transport, and so on.

NANWEP is ground-based, of course. There are also airborne weather
computers like those of the U.S. Weather Bureau’s National Severe Storm
Research Aircraft Project. The Weather Bureau has jumped its computer
budget from $1.5 to $2.5 million to extend this and other projects. The
compact airborne computers ride along in DC-6 and B-57 aircraft to
monitor hurricanes off Florida and tornadoes in the Great Plains area.
The computers gather forty different kinds of information and convert it
to digital form at thousands of characters a second. Such monitoring of
violent weather by means of computers suggests an intriguing use of the
machine. Man has long considered the prospect of going the step beyond
weather recording and prediction to actually changing or even creating
his own weather. He has done a few rather startling things of this kind,
admittedly on a small scale but with tremendous implications.
Cloud-seeding experiments are samples, as attempts both to induce
precipitation and to create or destroy storms. These experiments, though
inconclusive, have led to results—including precipitation of lawsuits
and ill feeling. Meteorologists attempted to divert a hurricane along
the Atlantic coast line once, apparently with results. But the storm
swerved too far and the weathermen incurred the justifiable wrath of
those living in the area affected. Why not simulate such an experiment
in the computer? Besides being safer, it is also far cheaper. In the
long run, we may do something about the weather at that.


                          _Computers in Space_

There are many points in history when seemingly fortuitous happenings
take place. The invention of the printing press appears to have occurred
at a fork in the road as literature flowered. The discovery of gasoline
and the automobile went hand in hand. So it is with the electronic
computer and the spacecraft. Is the computer here because it was needed
for such an application, or did it actually cause the advent of space
flight? Our conclusions must depend on our belief or disbelief in such
things as causality. A realistic view might be merely to applaud and
appreciate the confluence of two important streams of thought to make a
river that will one day flow to the other planets and finally out of the
solar system entirely.

Putting even something so unsophisticated as a brick into orbit would
require the plotting of an exact trajectory handily done only by a
computer. Sending the Mercury capsule aloft obviously requires a more
refined aiming system, and its re-entry into the atmosphere demands a
nicety of calculation measured in a fraction of a degree. The same is
true for the Russian achievements in sending a space vehicle around the
moon, and manned capsules in prolonged orbit. Such navigation can be
planned and carried out only by the sophisticated mathematics of a
computer. Dr. Wernher von Braun has said that any effective
space-vehicle firing program would be impossible without computers and
computing techniques.

Not long ago, the mariner could leisurely brace himself on the deck of
his vessel and take a noon sight with his sextant. It mattered little if
it took him some time to work out the computations; his ship traveled at
only a few knots and in only two dimensions. Today the space capsule or
missile moves as far in a single minute as a ship might in an entire
day, and it moves not across the practically flat surface of the sea but
through three-dimensional space in which that third degree of freedom is
of vital importance. Not only must the navigation be done with fantastic
precision, it must be done in “real time” to be of any value. This is
true whether the mathematics is being done by a Mercury capsule or one
of our antimissile missiles. Just as Richardson’s weather prediction
three months after the fact was of little use, the trajectory of an
invading missile will avail us nothing if it takes us thirty minutes to
compute. The problem by then, for the survivors, will be one of fallout
and not blast.

For this reason a computer is aboard practically every space vehicle
that leaves the earth. The Atlas and Titan, the Minuteman and Polaris,
all are controlled by tiny digital computers in their innards,
supplemented by more complex machines on the ground. These ground
computers calculate the trajectory, then monitor the missile to correct
its course if necessary. Complex as these functions seem, they are
childishly simple by comparison with the kind of calculations that are
necessary for lunar or planetary flight.

A mathematician who knew his astronomy could work out the figures
necessary to launch a space craft on its flight to Venus, but he would
have to start some time before launching day. In fact, it would take
forty generations of mathematicians to do the job. The trip itself would
consume about four months. At the Jet Propulsion Laboratories of the
California Institute of Technology, this 800-year project is planned and
flown in thirty seconds by an IBM 7090 computer. For example, the
computer tells us that if we had blasted off bright and early on August
17, 1962, we could make it to the Clouded Planet at 10:09 A.M., December
9. The curved trip through space would cover 32,687,000 miles.

The computer, then, not only can perform in real time but can even
shrink time. The Venus trip is simulated daily at the Jet Propulsion
Laboratories, and tapes stored in the computer cabinets also bear the
names Moon, Mars, Saturn, Jupiter, and so on. When the day comes to make
the actual voyage, the odds are good that because of what scientists
have learned from the computer the trip will go as smoothly as all the
simulations. Rather than the planetary voyages, which are still some
time off, lunar soft landings will be among the first to demonstrate the
accuracy of simulations now being made by General Dynamics, whose
Atlas-Centaur will put the lunar rover Surveyor on the moon shortly.
Apollo, the three-man lunar spaceship, won’t be far behind.

Not long ago a computer was put to work to see if it could pare down the
costs of the Atlas and Thor rocket engines. We have to have such
defensive weapons, but the cheaper we can make them the more we can
afford. The economy program worked, reducing costs more than a third.


                               _Summary_

The computer is on the Washington payroll to stay, and it may well move
up the hierarchical ladder there. It was not a comedian but an M.I.T.
professor who recently suggested that the computer will replace the
bureaucrat. Contending that the computer is inherently more flexible
than the bureaucrat, Professor John McCarthy told an Institute of Radio
Engineers meeting that the machines will not regiment us. “On the
contrary, I think we can expect a great deal more politeness from
machines than we have gotten from humans,” he said. His views were
debated by other panelists, but the gauntlet seems to have been flung.
With a party affiliation, the computer may well run for president
someday!

[Illustration:

  Lichty, © _Field Enterprises, Inc._

  “It IS human, men!... Besides solving our problems of global strategy,
    it’s also beginning to jot down its memoirs!”
]


------------------------------------------------------------------------


“_Business may not be the noblest pursuit, but it is true that men are
bringing to it some of the qualities which actuate the explorer,
scientist, artist: the zest, the open-mindedness, even the
disinterestedness, with which the scientific investigator explores some
field of research._”

                    —Earnest Elmo Calkins




                8: The Computer in Business and Industry


The government, of course, is not the only user of the electronic
computer. Business is faced with the same problems as government, plus
others perhaps, and can use the same techniques in planning, producing,
merchandising, and keeping track of its products. To General Electric
goes the distinction of first installing the large-scale electronic
computer for its business-data processing. This was done quite recently,
in 1954. Commenting on the milestone, the _Harvard Business Review_ said
in part:

The revolution starts this summer at General Electric Company’s new
Appliance Park near Louisville, Kentucky. The management planning behind
the acquisition of the first UNIVAC to be used in business may
eventually be recorded by historians as the foundation of the second
industrial revolution; just as Jacquard’s automatic loom in 1801 or
Frederick W. Taylor’s studies of the principles of scientific management
a hundred years later marked turning points in business history.

It is early yet for comment from historians, but the growth of the
business computers from the pioneer UNIVAC bears out the theme of the
_Harvard Business Review_ suggestion. In 1961 there were 6,000 large
electronic computers in use; General Electric alone has more than 100.
One big reason for this is the fact that government is not alone in its
output of paperwork. It has been estimated that one-sixth of our Gross
National Product, or about $85 billion, is devoted to paper-handling. In
the time it takes to read this chapter, for example, Americans are
writing 4 million checks, and this is only a small part of the paperwork
involved in the banking business.

[Illustration:

  _General Electric Co., Computer Dept._

  First National Bank of Arizona personnel operate sorters during
    initial operation of a new GE-210 computer-controlled
    data-processing system. The sorters process bank checks at the rate
    of 750 per minute as printer (foreground) prints bank statements at
    900 lines per minute.
]

Wholesale banks have been called fiscal intelligence agencies, doing
business by the truckload, and measuring the morning mail by the ton.
Yet this information is dealt with not only in volume, but in precise
and accurate detail. If a client asks about the rating of a customer who
has just ordered several million dollars worth of goods, the bank may be
called on to furnish this information in a very short time, even though
the customer resides halfway around the world.

Since they deal in figures, it is logical that banks were among the
first businesses to be computerized. Many of us are aware of those
stylized numbers now on the bottom of most of our checks, and vaguely
conscious that through some mysterious juggling by computers called ERMA
and other such names banks balance our accounts at electronic speed.

Insurance companies were next in line as computer candidates. Like
banking, insurance is believed to have been available to Babylonian
merchants thousands of years ago. In those days there were fewer people,
and probably claims were fewer; the abacus was the only computer needed
to keep pace. But since insurance was introduced on the North American
continent, coincidentally in the same state, Pennsylvania, as banking,
it has been threatened with drowning in a sea of its own policies.

The computer is ideally suited for doing the work of the insurance
business. There is no question today that the computer has taken over
from the insurance clerk. One firm installed computers in 1953 and since
then has doubled its accounts and tripled dollar volume, without hiring
the 250 additional people who normally would have been required for such
an increase. Eight outlying offices have been closed, yet service is
better and faster, agents’ commissions are paid twice a month instead of
only once, and actuarial computations that once took six months are now
done in a week.

A computerized world is of course not without its problems. The computer
system is so efficient, in fact, that the same outcry is going up from
labor as was heard in the days of the first industrial revolution. It
has been said with some truth that automation upgrades jobs, and not the
workers themselves. The change-over from quill pen to pushbutton console
will take some time and cause some pain, but in the end our gain will be
as great a stride as we have made since the days of the introduction of
the first factories with their more efficient production methods. Surely
the business worker already has been freed from the tedium of adding
columns of figures and much filing, and given pleasanter work in
exchange.


                         _The Shopper’s Friend_

After banking and insurance, which businesses yield to the lure of
high-speed automatic data-processing? Department stores are dabbling,
and supermarkets too are beginning to use the computer. The A & P stores
are studying such a system, as is the Liggett Drug Company. At first the
computer looked attractive as an inventory and ordering tool; now it is
headed in the direction of automating the actual shopping operation.

In Paris, a retail grocer made merchandising history by displaying more
than 3,000 different items in a floor space of only 230 square feet. The
trick is in a punched-card system that automatically registers and
prices any item the buyer selects. At the check stand the card is run
through a computer which figures the bill and orders the groceries,
which are automatically selected from the warehouse and delivered in a
cart to the purchaser at the door!

A similar automatic supermart system is being pushed by Solartron—John
Brown, Ltd., in England. The computerized scheme works much like the
French one. The shopper inserts a card in the slot beside the item she
wants and a punch marks it in alpha-numeric code for item and price. If
more than one item is desired the card is reinserted. With each punch,
the machine slices off a bit of the edge of the card so that it slides
deeper into the slot next time. At the cashier’s station, the card is
placed in a computer. Fifteen seconds after she has paid for them, the
shopper is delivered her groceries. Besides the saving in time for the
shopper, there is a saving for the grocer in floor space and also the
elimination of the loss through shoplifting. About the only thing that
might seem to be against the new system is the psychology of the large
display, which motivation researchers tell us stimulates volume buying.

With this factor in mind, an official of Thompson Ramo Wooldridge, Inc.,
has suggested retaining the large stocks on display, but coding them
with fluorescent paint of certain wavelengths to correspond to price.
The shopper fills her cart even as in the conventional store, but at the
mechanized checkstand an electronic eye on the computer scans and prices
the items while they are being automatically packaged. The doubting
Thomases say of this system that the packager will probably put the eggs
on the bottom, along with the tomatoes and ice cream!

The advertising journal _Commercial Art_ comments sadly on this accepted
fact of automation in the market place:

The checkout clerk is doomed, that last survivor of human warmth in most
of today’s supermarkets. His eventual executioner will be the electronic
computer, of course. Pilot systems using computers for automatic
checkouts are already drawing a bead on the jovial little man in the
green smock. Eventually even he will disappear from the faceless canyons
of our sleek supermarkets.

But the writer finds a ray of hope in the conclusion of his editorial.

Skilfully designed packages can strike an emotional chord in the
consumer, can create strong brand preferences even in the absence of
product differences. Supermarkets can give the appearance of being a
friendly, “human” place to shop even if the only humans visible are the
customers.

To make more complete the rout of conventional merchandising by the
computer-oriented system is the plan to automate even the trading stamp.
American Premium Systems, Inc., a Texas firm, is developing a plan in
which the customer receives a coded plastic card instead of a stamp
book. When he makes a purchase, a card is punched with the number of
credits he has earned. By means of a centralized computer, an IBM 1401
in this instance, records are kept continuously, and when the customer
has accrued 1,500 points he receives a premium automatically. The
obvious advantage here is to the customer, who is spared the messy task
of licking thousands of evil-tasting multicolored stamps, and the danger
of losing the book before redemption. But the storekeeper profits too.
He does not risk the loss or theft of stamps, nor does he buy stamps for
people who are not going to save them. The complete system will call for
an IBM 7074 and represents an outlay of about $3 million to service some
6 million customer accounts.

Before leaving the area of merchandising, it might be well to mention
inventory management in general and the effect of the computer upon it.
Applying what is known as “conceptual order analysis,” one marketer who
is using computers in his business talks of “warehousing without bricks
or mortar.” With a confidence born of actual testing, his firm expects
one day to have _no_ inventory except that on his production lines or in
transit to a customer. This revolutionary idea is based on practically
instantaneous inventorying, production ordering, and delivery
scheduling. While the warehouse without bricks or mortar is not yet a
fact, research discloses many manufacturers who have already cut their
standing inventories, from small amounts to as much as 50 per cent,
while maintaining customer service levels. This was done using what by
now are “standard” electronic information-handling methods. The
implication here is of the computer not merely as a data-handler, but as
a business organizer and planner as well.


                        _Electronic Ticker Tape_

The stock market lends itself to the use of high-speed data-processing,
even though a Wall Street man achieved notoriety some time back as the
first embezzler to use computer techniques. Admittedly it is harder to
track down the hand in the till when it pushes buttons and leaves no
telltale fingerprints or handwriting, but computerization continues
despite this possible drawback. The same firm has added digital
computers to one of its offices for faster service. The American Stock
Exchange installed $3 million worth of new processing equipment to
provide instantaneous automatic reports on open, high, low, close, bid,
asked, and volume-to-the-moment figures.

[Illustration:

  _International Business Machines Corp._

  On the floor of the New York Stock Exchange, representatives of
    Thomson & McKinnon and IBM discuss a model of the computing system
    which will speed transactions from the offices of the brokerage
    houses in 41 cities to the New York and American stock exchanges.
]

The stock market’s need for the computer lies in the usual two factors:
tremendous paperwork and increasing pressure for speed. Trading of stock
amounts to about three-fourths of a billion shares in a year, and
occasionally 3 million shares a day change hands. A major brokerage
house has confirmations to handle on thousands of trades, dividends to
credit to nearly half a million active accounts, and security position
and cash balances to compute for each customer. The increasing amount of
business, plus the demand for more speed and accuracy, make the computer
the only solution.

Simply reporting the results of the day’s marketing in the newspapers is
a monumental task. The Associated Press is installing a system based on
an IBM 1620 computer, in which ticker information will also be given in
the computer for sorting, comparison, tabulation, and storage. At the
correct time, the machine will print out the format for publication in
the press at the rate of 4,500 words a minute. With a memory of 20
million characters and a capacity for 600,000 logical decisions each
minute, the computer keeps up with stock information practically as fast
as it is received, and even a late ticker will not mean a missed
newspaper deadline. Associated Press expects to be able to transmit the
stock-market results to its papers within fifteen seconds after the
ticker closes. Not just in the United States but in Japan as well, the
computer is invading the stock market. The abacus is out, and now the
exchange in Tokyo is using an advanced UNIVAC solid-state computer to
process transactions.


                         _Versatile Executive_

It is this high-volume capacity, speed, and accuracy that makes the
computer a welcome new employee in most business operations. An example
is the Johnson’s Wax system linking its facilities for rapid management
reaction to changing conditions. Headquarters is linked to twenty three
warehouses and sales offices, and today’s work is based on yesterday’s
inventory instead of last month’s.

Computers schedule hotel reservations, and handle accounts payable and
receivable for the hotel industry. Auto-parking, now a $500 million a
year business, leans ever more heavily on computers for ticket-issuing,
car-counting, traffic direction, charge-figuring, and collection. The
freeway too has its computers, though there have been minor setbacks
like that on the New Jersey Turnpike where an automatic toll-card
dispenser was mistaken by slow-thinking people for a collector and its
working was jammed with coins and battered by abuse when no change was
forthcoming! Man will take some educating as the machine finds wider
employment.

The computer has been seen in the publishing business primarily as a
tool for searching lists and printing addresses. Now it is beginning to
take over more important duties such as typesetting. The new daily
_Arizona Journal_ is the first newspaper to make use of this technique.

From use in other businesses, the computer has grown to fostering a
business of its own. An example is in the production of payroll checks
by specialty firms, and safeguarding against bad checks with such
services as Telecredit, a computer-run system that spots bad checks upon
interrogation from its member stores.

In Waterbury, Connecticut, a computer helps home-buyers and realtors by
listing all available homes in the area. Three reports are produced: a
total listing, a listing by style, and a listing by price. Bell
Telephone in New York uses a computer system to deliver its 9 million
directories to subscribers in the city and suburbs. The rapid system
permits changing of delivery orders even while the books are at the
printers. A computer method of making sausage recipes is now available
to all packers. Remington Rand developed this application at its UNIVAC
Center on the campus of Southern Methodist University.


                            _Communication_

Communication is a vital part of all business, and the digital computer
finds another application here. A technique known as adaptive control
was recently presented at a symposium by scientists from IBM.
Special-purpose computers integrated into communication networks would
make possible the “time-sharing” of channels and cut costs per message
sharply. Another digital computer, an inexpensive “decision threshold”
device, is being pushed as a means of reducing errors in the
transmission of messages. These logical uses of the computer were
presaged in the 30’s when Shannon wrote his pioneering circuit-logic
paper, and in the late 40’s with his work on information theory.

TV Station KNXT in Los Angeles uses a digital computer to control the
complicated switching necessary during station breaks. This electronic
juggling of live shows, commercials, and network programming is called
TASCON, for Television Automatic Sequence Control. It can be programmed
hours before use, and then needs only the push of the button instead of
frantic manual switching that occasionally throws the human operator.

Not just the mechanics of transmitting the commercials on TV, but even
the billing and other accounting functions are a major computer project.
To handle close to $700 million a year in payments, an IBM 7090 computer
is being used. There are more than 5,000 TV stations in the country,
with billings dependent on a complicated structure of 180 different
rates. As a result, there is an undesirable lag in payment. Putting
records on tape and feeding them to the computer is expected to clear up
the trouble and provide a bonus in the form of advising stations on
discount rates for programming on a current basis.

The computer isn’t content with skirting the edges of the advertising
game, of course. A heated battle is going on now in this industry over
the growing use of the computer to plan campaigns and actually evaluate
ads, a task held by some to be the exclusive domain of the human adman
with his high creative ability. The Industrial Advertising Research
Institute triggered the fight by using a computer to study 1,130
advertisements appearing in the industrial journal _Machine Design_ and
select the best black-and-white and the best color ads.

While diehards snorted ridicule, the computer made its choices. IARI
then compared its selections with those made by two of the largest and
most experienced rating firms. On color ads, the computer scored 66 per
cent, rating two out of three ads practically the same as the human
selectors. With black-and-white it did even better, scoring 71 per cent.
Its detractors, assuming of course that the human raters were
infallible, gloated that the computer was a flop, that it could pick
only the average ads accurately and fell down on excellent and poor
ones.

The agency of Batten, Barton, Durstine & Osborn thought otherwise and is
using the computer in its advertising. As a tool for media selection and
scheduling, BBDO likened the computer to a power shovel instead of a
spade. The new method makes it possible to compare thousands of
combinations a second. Another firm, the Simulmatics Corporation, agrees
with BBDO. The computer, it says, will permit advertising campaigns far
more effective than those waged at present, since the most efficient
campaign may be too complex to be devised without artificial aid. The
key to the Simulmatics system is the “media mix model” in which a
hypothetical campaign can be tried out in advance in the computer.

Young & Rubicam differs hotly with computer advocates. A spokesman
leveled a low blow at the computer, suggesting that it will have
difficulties forming motivational research based on Freudian analyses!
The firm says no way has yet been found to transpose “Viennese
fatuities” into Arabic numerals. It deplores the turning of a
media-planner into a rubber stamp as media selection becomes an
automatic reiteration which “those with an abacus could pipe to a stale
and sterile tune.” The battle rages, but the outcome seems to be a
foregone conclusion. Either the computer will sway Madison Avenue from
Viennese fatuities, or it will learn about sex.


                               _Industry_

We have discussed the computer in business; perhaps it would be well to
stress that this includes industry as well. The computer not only
functions in the bank and brokerage house, insurance office, and
supermart, but also is found increasingly in jobs with oil refineries,
chemical plants, surveying teams, knitting mills (a likely application
when we remember Jacquard), and steel mills. As automation takes over
factories, it brings the computer with it to plan and operate the new
production methods. Transportation too is making good use of the
computer. Freight-handling in the United States, Canada, England, and
the U.S.S.R. is using machine techniques.

Our high-speed airplanes are already more aimed than flown, and less and
less seen and seen from. Mach-3 aircraft are on the drawing boards now,
aircraft that will fly at three times the speed of sound or about 2,000
miles per hour. An airliner taking off from London must already be
cleared to land in New York. So authorities on both sides of the ocean
are concerned. In England, giant computers like the Ferranti Apollo and
others are on order. There is talk in that country too of integrating
military and commercial aviation into one traffic control system. In the
next ten years the sky population may double again, in addition to
flying faster, further crowding the airlanes and particularly the space
adjacent to airports. The only solution to this aerial traffic jam lies
in the electronic computer.

Not as spectacular as air traffic control, but important nonetheless, is
the job of planning the route an airliner will fly. United Air Lines
uses a Bendix G-15 to select flight plans for its big DC-8’s. In a
manner similar to the NANWEP course-planning described for surface
vessels, the computer examines a number of possible routes for the big
transports, considering distance flown, wind, temperature, weight and
fuel requirements, and time schedules.

This flight-planning was originally done by manual computation and
required an hour to work out details for only one possible flight plan.
The computer method was demanded because of the increased speed of the
big jets and their sensitivities to weather conditions en route. The
computer examines a number of tentative plans in minutes and selects the
one which will make the optimum use of winds aloft, temperatures,
weather, and so on. If weather changes en route require it, the pilot
can call the planning center no matter where he is and request that the
computer work out a new flight plan.

Once the optimum flight plan has been figured, an electronic computer in
the aircraft itself may one day assure that the desired flight path is
actually flown. The ASN-24 computer, developed by Librascope,
Incorporated, and the Air Force, weighs only thirty-one pounds, yet
performs more than 20 million computation steps in a six-hour flight.
The electronic navigator, with information from Doppler equipment and
other navigation aids, evaluates which is the best “fix,” weighing for
example the relative accuracies of a Loran fix and a dead-reckoning fix.
The computer even shoots celestial fixes and plots the results!
Obviously faster than its human monitor, the electronic navigation
computer solves navigation problems with an error as small as one part
in 32 million.

A broader use of the computer in aircraft is proposed by the Convair
Division of General Dynamics. Because today’s airplane is far more
complicated than those ten years ago, and those ten years hence will
extend this trend, the firm feels that checkout of the aircraft will
require electronic computers. While adding about 3 per cent to the total
cost of the plane, such equipment could perform a variety of functions
including maintenance analysis and would add an hour a day to the
profit-making flight time.

There would be no profit for the airlines with the best flight planning
and in-flight control in the world if there were no passengers aboard;
the “traffic problem” extends from the sky to the ticket counter. For
this reason most airlines have already recruited the computer for
another important job—that of ticket reservation clerk. An example,
recently installed by United Airlines, is the “Instamatic,” a giant,
far-flung system weighing 150 tons and requiring 12,000 miles of
circuits. Instamatic cost $16 million and can handle 540,000
reservations in a single day. So complex is the computer system that it
requires 40,000 printed-circuit boards, 500,000 transistors, and
2,000,000 ferrite memory cores. But it gets the job done, and any one of
3,000 agents all over the country can confirm space on any flight,
anytime, within seconds!

There are other systems used by competing lines, systems called Sabre,
Teleflite, and so on. But Remington Rand UNIVAC has proposed an over-all
system that will make any of them look like a child’s do-it-yourself
walkie-talkie. The UNIVAC plan is for a single interline reservation
system, used by all twenty-four domestic airlines. Called AID, for
Airline Interline Development, the new scheme would cost the airlines
only 12 cents per message, and could be tied in with foreign carriers
for international bookings.

[Illustration:

  _Remington Rand UNIVAC_

  Console for airlines reservation system permits pushbutton booking of
    space.
]

Present methods of reservations among airlines require from less than a
minute for easy bookings to several hours for the tough ones. The AID
system uses a dial phone, with direct lines to a central computer in
Chicago. The response to the dialed request is an immediate voice
answer. If space is available, the computer also stores all the needed
information for the reservation and transmits a teletype message to the
boarding point of the proper airline.

To go back another step, the aircraft on which the computer confirms
seat space was most likely built with the help of another computer. A
typical production system is that used by Lockheed in its Marietta,
Georgia, plant. There an IBM 305 RAMAC computer keeps track of 45,000
parts orders continuously. The result is better and faster operation,
and a saving to Lockheed of $3,500 a month. In California, Lockheed is
using a computerized data acquisition system called EDGE, for Electronic
Data Gathering Equipment, that feeds production information directly
into a computer memory for analysis and action orders. Remote reporting
stations can be operated by production-line workers and will relay
production data to the central computer. Although the Lockheed EDGE
system will cost more than $600,000 a year, officials feel that it will
save the company three times that at the outset, and perhaps more when
wider use is made of its potential. An interesting feature is the tying
together of Lockheed’s widely separated plants at Sunnyvale, Palmdale,
and Van Nuys, California.

North American Aviation links its complex of plants in the Los Angeles
area by microwave, even bouncing beams of data from reflectors atop Oat
Mountain where there is no direct line-of-sight path between the
different locations. Douglas Aircraft maintains a data link between
California and Charlotte, North Carolina, to permit use of computers
over a distance of 2,400 miles.

The airlines are also using computer inventory systems to control their
stock of spare parts. Material costs represent 60 per cent of airline
revenue and are rising; some larger carriers have investments of as much
as $75 million in spare parts. It takes the computer to control the flow
of repairable parts through the shop efficiently, schedule the removal
of those requiring periodic checks, spot high-use items, and so on.

As an example of the complexity a large airline faces in its
maintenance, TWA stocks 8,000 different replaceable items. When such
parts are needed, they must be on hand _where_ they are needed, but
overstocking can lead to financial ruin. To match increasing
competition, airlines find it necessary to resort to the laws of
probability and other sophisticated statistical techniques in stocking
parts. Fed such equations, the computer can match ten to twelve
man-years of work in three hours, and mean the difference between an
oversupply of parts in New York with outages in Los Angeles, and
properly balanced stocks.

The ramifications of the computer in the airplane industry are
far-reaching. For example, Boeing has recorded the lessons it learned on
its Bomarc missile program in computers so that it can retain and apply
them on its Minuteman and Dyna-Soar programs. The computer will thus
keep track of men and their projects and warn them of previous mistakes.
Modern management techniques such as PERT and PEP, favored by the
government, make good use of the computer.

The McDonnell Aircraft Corporation is primarily a builder of planes and
space vehicles, but it has found itself in the computer business too as
a data-processing center. Installing computers for its own engineering
and business uses, McDonnell soon began selling computer time in off
hours to banks and other businesses. It now has a computer valuation of
about $10 million and operates around the clock.


                        _The Designing Computer_

It seems strange that the computer was a bookkeeper and clerk for years
before anyone seriously considered that it might be an engineer as well,
yet the men who themselves designed the computer were loath to use it in
their other work. Part of this resistance stems from the high premium
placed on the creativity of research and design work. The engineer uses
science in his work, to be sure, but he professes to use it as an
artist, or with the personal touch of, say, a brewmaster. There is
another possible reason for the lag in computer use by the men who
should appreciate its ability the most. In the early days of the
computer, it clacked away all week figuring payrolls, and perhaps
writing checks. That’s what it was ordered for, and that’s where the
money was—in the businessman’s application of the computer.

To be sure, the military was using the computer for other purposes, but
the average scientist or engineer not employed by Uncle Sam had access
to an electronic computer only on Sunday, if at all, when the big
machine had done its primary work and could take a breathing spell. To
further compound excuses for the foot-dragging engineer, there was a
difference in needs in payroll computation and scientific mathematical
calculation. Commercial computers are designed for a high rate of input
and output, with a relatively slow arithmetic going on inside. The
engineer, on the other hand, might need only several minutes of computer
time, but it could take him a couple of days to put the problem into a
form the machine could digest.

Slowly, however, enough engineers fought the battle of translation and
forewent Sunday pursuits like church, picnics, and golf to learn
haltingly how to use the electronic monster. It took courage, in
addition to sacrifice, because the computer was pooh-poohed by some
sharp scientific brains as an _idiot savant_ at best. Behind the inertia
there could have been a touch of concern too—concern that the machine
just might not be as stupid as everybody kept saying it was.

Heavy industry made use of the machines. The steel plants, petroleum and
chemical plants, and even the designers of highways were among the early
users of computer techniques. There was of course good reason for this
phenomenon. Faced with problems involving many variables and requiring
statistical and probabilistic approaches, these people could make the
best use of machines designed for repetitive computations. The refiner
with a new plant in mind could simulate it in the computer and get an
idea of how, or if, it would work before building his pilot plant. Today
the notion of dispensing with even the pilot plant is getting serious
consideration.

One program used by a gasoline producer analyzed thirty-seven variables
and thirty-seven restrictions, a matrix that could never be evaluated by
ordinary methods. Textile fiber research is another example, with thread
tests run on dozens of samples and averaged statistically for valid
conclusions. B. F. Goodrich put the computer to work in its laboratories
at such tasks as multiple-regression studies of past production of
processes like polymerization and the running of a batch of new material
on the computer.

These applications were accomplishing a two-fold benefit. First, years
were being telescoped into weeks or even days; second, _complete_
investigation rather than sketchy sampling was possible. Optimum
solutions took the place of the guesswork once necessary because of the
lack of sufficient brainpower to run down all the possibilities. Still
there were scientists and designers in other fields who shook their
heads loftily and said, “Not for me, thanks.” The computer was but a
diligent clerk, they held, relieving the engineer of some onerous
chores. It could do nothing really creative; that must be left to man
and his brain.

By now many industrial firms had purchased or rented computers for the
technical people so that they would not have to fight for a place in
line at the payroll computer. Civil engineering agencies, perhaps a
hundred strong, used computers to design bridges and plan and lay out
highways. Designers at the Tudor Engineering Company of San Francisco
put its Bendix G-15D to work planning the highway that Contra Costa
County will need in 1980. Almost all of our fifty states now use
computers in their highway departments. In 1960, Georgia solved more
than a thousand highway bridge design problems in its computers. Besides
doing the work faster and cheaper, the computer produces a safer
product. For example, if substandard materials are programmed in, the
computer will print out a warning or even stop working altogether so
that the error can be corrected.

Steel companies, like Jones & Laughlin, use computers not only to run
production mills, but also as research tools. Three hours of operation
of a new furnace can be simulated in the computer in thirty seconds.
Tracing the steel back to its ore, the computer is used again. The
Bureau of Mines has used the machines for several years; they are
helpful in problems ranging from open-pit operation, grades of ore,
drill-core data logging, reserve calculations, and process control.

[Illustration:

  _General Electric Co., Computer Dept._

  Computer operation of Jones & Laughlin steel mill.
]

Gradually, then, the resistance was worn down. Grudgingly at first, and
accepting the computer only as an assiduous moron, engineers in other
fields put it to work. Complex machine operations like gear-shaping were
planned and carried out by computers that even punched out tapes for
controlling the production tools. Optics designers switched from desk
calculators to electronic computers. Mechanical engineers in jobs from
ultrasonic vibrators to tractor design became users of computers. Mass
spectrometry, heat-exchanger design, and waterworks design joined the
jobs the computer could do.

The computer had figured in plotting trajectories for missiles, and in
the production of aircraft; engineers found it could design them too.
Back in 1945, an analysis of twenty-one different flight conditions at
each of twelve stations of an airplane fuselage took 33 days and cost
more than $17,000. Today, by using a high-speed computer instead of a
desk calculator, the analysis is completed in a day and a half, at a
cost of $200!

The last of the diehards seemed to be the electronics people themselves.
A survey conducted by a technical journal in the field showed that in
1960 many designers were not using computers in their work. Admitting
that the computer was a whiz just about everywhere else, the electronics
engineer still could say, “The machine is great on paperwork, but I do
_creative_ work. The computer can’t help me.” Other reasons were that
computers were expensive, took much time to program, and were helpful
only with major design problems. Fortunately, all designers do not feel
that way, and progress is being made to put the computer to work in the
electronics field. It is helping in the design of components (Bendix
saves ten man-hours in computing a tenth-order polynomial and associated
data) and of networks (Lenkurt Electric saves close to 250 engineering
hours a week in filter network design). Bell Telephone uses the computer
approach in circuit analysis, and Westinghouse in the design of radar
circuitry. It is interesting that as we move up the design scale, closer
to what the engineer once considered the domain of human creativity, the
computer still is of great value. In systems design it is harder at the
outset to pin down the saving in time and the improvement in the system
(the latter is perhaps hard to admit!) but firms using computers report
savings in this field too.

One interesting job given the computer was that of designing the
magnetic ink characters to be used in its own “reading” applications.
This project, conducted by Stanford Research Institute, is typical of
the questions we have begun to ask the computer about its needs and ways
to improve it. A larger scale application of this idea is that of
letting the computer design itself. Bell Telephone Laboratories
developed such a system, called BLADES, for Bell Laboratories Automatic
Design System, to design a computer used in the Nike-Zeus antimissile
defense system.

A wag once noted that the computer would one day give birth to an
electronic baby. His prophecy came true perhaps quicker than he
anticipated, but there is one basic difference in that the progeny is
not necessarily a smaller machine. The giant LARC, for instance, was
designed by lesser computers. As A. M. Turing has pointed out, it is
theoretically possible for a simple computer to produce a more complex
one. This idea is borne out in nature, of course, and man is somewhat
advanced over the amoeba. Thus the implication in the computer-designed
computer is far more than merely the time and money saved, although this
was certainly a considerable amount. The BLADES system in twenty-five
minutes produced information for building a subassembly, a job that
required four weeks of manual computation.

Notable improvements in the general-purpose computer are doing much to
further its use as a technical tool. Present machines do jobs as varied
as the following: personnel records, inventorying, pattern
determination, missile system checkout, power-plant control, system
simulation, navigation, ballistic trajectory computations, and so on.
Special computers are also provided now for the engineer; and among
these is the Stromberg-Carlson S-C 4020 microfilm recorder. Engineering
specifications are put into the computer and the machine can then
produce on request mechanical drawings as required by the engineer. Data
stored in the memory is displayed on a Charactron tube. There is little
resistance to this type of computer, since the engineer can say it is
doing work below his level of ability! Of course, the draftsman may take
a dim view of computers that can do mechanical drawing.

[Illustration:

  _Bell Telephone Laboratories_

  Engineer checks design information for first computer built from
    complete information furnished by another computer. Shown is a
    subassembly of the computer, which will be used in the Army’s
    Nike-Zeus antimissile defense system.
]

After a rather hard to explain slow start, then, the computer is now
well established as a scientific and engineering tool. Blue-sky schemes
describe systems in which the engineer simply discusses his problem with
the machine, giving specifications and the desired piece of equipment.
The machine talks back, rejecting certain proposed inputs and suggesting
alternatives, and finally comes up with the finished design for the
engineer’s approval. If he laughs overly loud at this possibility, the
engineer may be trying to cover up his real feelings. At any rate the
computer has added a thinking cap to its wardrobe of eyeshade and work
gloves.


                            _Digital Doctor_

Medical electronics is a fairly well-known new field of science, but the
part being played in medicine by the computer is surprising to those of
us not close to this work. Indicative of the use of the computer by
medical scientists is a study of infant death rates being conducted by
the American Medical Research Foundation. Under the direction of Dr.
Sydney Kane, this research uses a UNIVAC computer and in 1961 had
already processed information on 50,000 births in ninety participating
hospitals. Punched-card data include the mother’s age, maternal
complications, type of delivery, anesthetics used, and other pertinent
information. Dr. Kane believes that analysis by the computer of this
information may determine causes of deaths, after-birth pathological
conditions, and incapacity of babies to reach viability. A reduction in
infant mortality of perhaps 12,000 to 14,000 annually is believed
possible as a result of the studies.

Another killer of mankind, cancer, is being battled by the computer.
Researchers at the University of Philadelphia, supported in part by the
American Cancer Society, are programming electronic computers to act as
cancer cells! The complexity of the problem is seen in the fact that
several man-years of work and 500 hours of computer programming have
barely scratched the surface of the problem. A third of a million
molecules make up the genes in a human cell, and the actions of these
tiny components take place many times faster than even the high-speed
computer can operate. Despite the problems, some answers to tough
chemical questions about the cancer cells are being found by using the
computer, which is of course thousands of times faster than manual
computation.

If you were discharged from a hospital in 1962, there is a chance that
your records are being analyzed by a computer at Ann Arbor, Michigan as
part of the work of the Commission on Professional and Hospital
Activity. Information on 2-1/2 million patients from thirty-four states
will be processed by a Honeywell 400 computer to evaluate diagnostic and
hospital care and to compare the performance of the various
institutions.

In the first phase of a computerized medical literature analysis and
retrieval system for the National Library of Medicine, the U.S. Public
Health Service contracted with General Electric for a system called
MEDLARS, MEDical Literature Analysis and Retrieval System. MEDLARS will
process several hundred thousand pieces of medical information each
year. New York University’s College of Engineering has formed a
biomedical computing section to provide computer service for medical
researchers. Using an IBM 650 and a Control Data Corporation 1604, the
computer section has already done important work, including prediction
of coronary diseases in men under forty.

The success of computers in these small-scale applications to the
problems of medicine has prompted the urging of a national biomedical
computer system. It is estimated that as yet only about 5 per cent of
medical research projects are using computer techniques, but that within
ten years the figure will jump to between 50 and 75 per cent.

An intriguing possibility is the use of the computer as a diagnostic
tool. Small office machines, costing perhaps only $50, have been
suggested, not by quacks or science-fiction writers, but by scientists
like Vladimir Zworykin of the Rockefeller Institute of Medical Research.
Zworykin is the man who fathered the iconoscope and kinescope that made
television possible. The simple diagnostic computer he proposes would
use information compiled by a large electronic computer which might
eventually catalog the symptoms of as many as 10,000 diseases. Using an
RCA 501 computer, a pilot project of this technique has already gathered
symptoms of 100 hematological diseases.

Another use of the computer is in the HIPO system. Despite its
frightening acronymic name, this is merely a plan for the automated
dispensing of the right medicine at the right time to the right patient,
thus speeding recoveries and preventing the occasional tragic results of
wrong dosage. More exotic is a computer called the Heikolator which is
designed to substitute for the human brain in transmitting messages to
paralyzed limbs that could otherwise not function.

The simulation of body parts by the computer for study is already taking
place. Some researchers treat the flow of blood through arteries as
similar to the flow of water through a rubber tube, analyze these
physical actions, and use them in computer simulation of the human
system. The Air Force uses a computer to simulate the physical chemistry
of the entire respiratory and circulatory systems, a task that keeps
track of no less than fifty-three interdependent variables.

Dr. Kinsey of the Kresge Eye Institute in Detroit is directing computer
work concerning the physiology of the eye. According to Kinsey it was
impossible previously to approximate the actual composition of cell
substances secreted from the blood into the eye. Even those whose eyes
no longer serve them are being benefited by computer research. The
Battelle Memorial Institute in Columbus, Ohio, uses an IBM computer to
develop reading devices for the blind. These complicated readers use a
digital computer to convert patterns of printed letters into musical
tones. Further sophistication could lead to an output of verbalized
words. Interestingly, it is thought that the research will also yield
applications of use in banking, postal service, and other commercial
fields.

Russia is also aware of the importance of the computer in the medical
field. A neurophysiologist reported after a trip to Russia that the
Soviet Union is training its brightest medical students in the use of
the computer. Such a philosophy is agreed to by medical spokesmen in
this country who state that no other field can make better use of the
computer’s abilities. Among advanced Russian work with computers in the
biomedical field is a study of the effects on human perception of
changes in sound and color.

Visionary ideas like those of radio transmitters implanted in patients
to beam messages to a central computer for continuous monitoring and
diagnosis are beginning to take on the appearance of distinct
possibilities. Some are beginning to wonder if after it has learned a
good bedside manner, the computer may even ask for a scalpel and a TV
series.


                                _Music_

The computer has proved itself qualified in a number of fields and
professions, but what of the more artistic ones? Not long ago RCA
demonstrated an electronic computer as an aid to the musical composer.
Based on random probability, this machine is no tongue-in-cheek gadget
but has already produced its own compositions based on the style of
Stephen Foster. Instead of throwing up their hands in shocked horror,
modern composers like Aaron Copland welcome the music “synthesizer” with
open arms. Bemoaning only the price of such a computer—about
$150,000—Copland looks to the day when the composer will feed in a few
rough ideas and have the machine produce a fully orchestrated piece. The
orchestration, incidentally, will include sounds no present instruments
can produce. “Imagine what will happen when every combination of
eighty-eight keys is played,” Copland suggests. Many traditionalists
profess to shudder at the thought of a machine producing music, but
mathematical compositions are no novelty. Even random music was
“composed” by Mozart, whose “A Musical Dice Game” is chance music with a
particularly descriptive title, and Dr. John Pierce of Bell Laboratories
has extended such work.


[Illustration:

  Taken from “_Illiac Suite_,” by L. A. Hiller
    and L. M. Isaacson, copyrighted 1957, by
    _Theodore Presser Co._ Used by permission.

  Random chromatic music produced by ILLIAC computer
  resembles the compositions of some extreme modern composers.
]


In 1955, Lejaren A. Hiller, Jr., and L. M. Isaacson began to program the
ILLIAC computer at the University of Illinois to compose music. The
computer actually published its work, including “Illiac Suite for String
Quartet,” Copyright 1957, New Music Editions, done in the style of
Palestrina. All music lies somewhere between the complete randomness of,
say, the hissing of electrons in vacuum tubes and the orderliness of a
sustained tone. No less a master than Stravinsky has called composition
“the great technique of selection,” and the computer can be taught to
select in about any degree we desire. Hiller describes the process, in
which the machine is given fourteen notes representing two octaves of
the C-major scale, and restricted to “first-species counterpoint.” By
means of this screening technique, the computer “composed” by a
trial-and-error procedure that may be analogous to that of the human
musician. Each note was examined against the criteria assigned; if it
passed, it was stored in memory; if not, another was tried. If after
fifty trials no right note was found, the “composition” was abandoned,
much as might be done by a human composer who has written himself into a
corner, and a new start was made. In an hour of such work, ILLIAC
produced several hundred short melodies—a gold mine for a Tin Pan Alley
tunesmith! It was then told to produce two-voice counterpoint for the
basic melodies. “Illiac Suite” is compared, by its programmers at least,
with the modern music of Bartok.

Purists whose sensibilities are offended by the very notion of computer
music point out that music is subjective—a means of conveying emotion
from the heart of the composer to that of the listener. Be that as it
may, the composition itself is objective and can be rigorously analyzed
mathematically, before or after the fact. From a technical standpoint
there seems to be only one question about this new music—who composed
it, the programmer or the computer?

An interesting sidelight to computer music is its use to test the
acoustics of as yet unbuilt auditoriums. Bell Telephone Laboratories has
devised such a machine in its Acoustical and Visual Research Department.
The specifications of the new auditorium are fed into the computer,
followed by music recorded on tape. The computer’s output is then this
music as it will sound in the new hall. Critical experts listen and
decide if the auditorium acoustics are all right, or if some redesign is
in order.


                         _The Machine at Play_

The computer’s game-playing ability in chess and other games has been
described. It is getting into the act in other fields, spectator sports
as well. Baseball calls on the computer to plan season strategy and
predict winners. When Roger Maris began his home-run string, an IBM 1401
predicted that he had 55 chances in 100 of beating Ruth’s record.
Workers at M.I.T. have developed a computer program that answers
questions like “Did the Red Sox ever win six games in a row?” and “Did
every American League team play at least once in each park in every
month?”

An IBM RAMAC computer is handling the management of New York’s Aqueduct
race track, and promises to do a better job than the human bosses, thus
saving money for the owners and the State of New York Tax Commission.
The Fifteenth Annual Powderpuff Derby, the all-women transcontinental
air race, was scored by a Royal Precision LGP-30 computer, and sports
car enthusiasts have built their own “rally” computers to gauge their
progress. The Winter Olympics at Innsbruck, Austria, will be scored by
IBM’s RAMAC, and even bowling gets an assist from the computer in the
form of a scoring device added to the automatic pin-setter, bad news to
scorekeepers who fudge to boost their points.

An IBM 704 has proved a handy tool for blackjack players with a system
for winning 99 per cent of the time, and rumor has it that a Los Angeles
manufacturer plans to market a computer weighing only two pounds and
costing $5, for horse-players.

Showing that the computer can be programmed with tact is the
demonstrator that answers a man’s age correctly if he answers ten
questions but announces only that a woman is over twenty-one. Proof that
the computer has invaded just about every occupation there is comes to
light in the news that a Frankfurt travel agency uses a computer called
Zuse L23 as an agent. The traveler simply fills out a six-question form,
and in a few seconds Zuse picks the ideal vacation from a choice of 500.
Computers, it seems, are already telling us where to go.


                           _Business Outlook_

The computer revolution promises to reach clear to the top of the
business structure, rather than find its level somewhere in middle
management. The book, _Management Games_ lists more than 30,000 business
executives who have taken part in electronic computer management “games”
in some hundred different versions. The first widely used such game was
developed in 1956 by the American Management Association. While such
games are for educational purposes, their logical extension is the
actual conduct of business by a programmed computer.

In his book, _Industrial Dynamics_, Dr. J. W. Forrester points out that
a high-speed digital computer can be used in analyzing as many as 2,000
variables such as costs, wages, sales, and employment. This is obviously
so far beyond human capability that the advantage of computer analysis
becomes evident. A corollary benefit is the speed inherent in the
computer which makes it possible to test a new policy or manufacturing
program in hours right in the computer, rather than waiting for months
or years of actual implementation and possible failure. For these
reasons another expert has predicted that most businesses will be using
computer simulations of their organizations by 1966. Regardless of the
timetable, it is clear that the computer has jumped into business with
both its binary digits and will become an increasingly powerful factor.

[Illustration:

  Lichty, © _Field Enterprises, Inc._

  “Our new ‘brain’ recognizes the human factor, doctor!... After feeding
    it the symptoms, it gives the diagnosis and treatment.... But YOU
    set the fee!”
]


------------------------------------------------------------------------


“_Men have become the tools of their tools._”

                    —Thoreau




                     9: The Computer and Automation


In his movie, _City Lights_, Charlie Chaplin long ago portrayed the
terrible plight of the workman in the modern factory. Now that the
machine is about to take over completely and relieve man of this
machinelike existence, it is perhaps time for Charlie to make another
movie pointing up this new injustice of civilization or machine’s
inhumanity to man. It seems to be damned if it does and damned if it
doesn’t.

For some strange reason, few of us become alarmed at the news of a
computer solving complex mathematics, translating a book, or processing
millions of checks daily, but the idea of a computer controlling a
factory stimulates union reprisals, editorials in the press against
automation, and much general breast-beating and soul-searching.
Perversely we do not seem to mind the computer’s thinking as much as we
do its overt action.

It is well to keep sight of the fact that automation is no new
revolution, but the latest development in the garden variety of
industrial revolution that began a couple of centuries ago in England:

Mechanization was the first step in that revolution, mechanization being
the application of power to supplement the muscles of men. Mass
production came along as the second step at the turn of this century. It
was simply an organization of mechanized production for faster, more
efficient output.

Automation is the latest logical extension of the two earlier steps,
made possible by rapid information handling and control. Recent layoffs
in industry triggered demonstrations, including television programs,
that would indicate we suspect automation of having a rather cold heart.
The computer is the heart of automation.

[Illustration:

  _Remington Rand UNIVAC_

  Control operations require “real-time” computers that perform
    calculations and make necessary decisions practically
    instantaneously.
]

None of these steps is as clear-cut or separate as it may seem without
some digging into history and an analysis of what we find. For example,
while we generally consider that the loom was simply mechanized during
the dawn of industrial revolution, the seeds of computer control were
sown by Jacquard with punched-card programming of the needles in his
loom. Neither is it sufficient to say that the present spectacle of
automated pushbutton machines producing many commodities is no different
from the introduction of mass-produced tractors. Tractors, after all,
displaced horses; the computer-controlled factory is displacing men who
don’t always want to be put out to pasture.

Automation is radically changing our lives. It is to be hoped that
intelligent and humane planning will facilitate an orderly adjustment to
this change. Certainly workers now toil in safer and pleasanter
surroundings. It is reported that smashed toes and feet, hernia, eye
trouble, and similar occupational accidents have all but disappeared in
automated automobile plants. Unfortunately other occupational hazards
are reportedly taking the place of these, and the psychological trauma
induced by removal of direct contact with his craft has given more than
one worker stomach ulcers. Let us investigate this transfer of contact
from man to computer-controlled machine.

A paper presented at the First Congress of the International Federation
of Automatic Control, held in Moscow in 1960, uses as its introductory
sentence, “Automatic control always involves computing.” The writer then
points out that historically the computing device was analog in nature
and tied so closely with the measuring and control elements as to be
indistinguishable as an actual computer. In more recent history,
however, the trend has been to separate the computer. With this trend is
another important change, that of using the digital computer in
automatic control.

One of the first papers to describe this separate computer function is
“Instrument Engineering, Its Growth and Its Promise,” by Brown,
Campbell, and Marcy, published in 1949. “Naturally,” the authors state,
“a computer will be used to control the process.” Not a shop foreman or
an engineer, but a computer. Watt’s “flyball” governor pioneered the
field; more recent and more obvious examples of control by computers
include ships guided by “Iron Mike” and airplanes flown by the automatic
pilot. These were analog devices, and the first use of a digital
computer as a control was in 1952, quite recently in our history. This
airborne digital control computer was built by Hughes and was called
“Digitac.”

Since most industries have been in existence for many years, far
antedating aviation, electronics, and the modern computer, the general
incorporation of such control has been difficult both because of the
physical problem of altering existing machines and the mental phenomenon
of inertia. Factory management understandably is slow to adopt a
revolutionary technique, and most control systems now in use in industry
are still analog in nature. However, where new plants are built from the
ground up for computer control, the results are impressive. Designed by
United Engineering, the Great Lakes 80-inch hot strip mill automatically
processes 25-ton slabs of steel. More than 1,000 variables are
controlled, and 200 analog signals and 100 digital computer-generated
signals are used in the process. The steel sheets are shot out of the
rolls at some 45 miles an hour, or about 66 feet a second! A human
supervisor would have a difficult job just watching the several hundred
signals related to thickness, temperature, quality, and so on, much less
trying to think what to do if he noticed something out of
specifications. This would be roughly analogous to an editor trying to
proofread a newspaper as it flashes by on the press and making
corrections back in the linotype room before any typographical errors
were printed. The new computer-controlled mill has an output of about
450,000 tons a month, twice that of the next largest in operation.

American control experts who attended the Moscow conference brought back
the information that Russian effort in computer control is greater than
that in the United States, and that the Russians are more aware of what
we are doing in the field than we are of their progress. Their
implementation of modern computer control may be made easier because
their industries are newer and do not represent such a long-established
and expensive investment in hard-to-modify existing equipment.

Basically, at least, computer control is simple and can be compared to
the feedback principle that describes many physical systems including
the workings of our own bodies. In practice, the computer can be put in
charge of producing something, and by sampling the output of its work
can constantly make corrections or improvements that are desired. This
is of course an extreme simplification, and the control engineer speaks
of “on-line” operation, of adaptive systems that adjust to a changing
environment, of predictive control, and so on. One vital requirement of
the computer involved in a control process, obviously, is that it cannot
take its time about its computations. The control computer is definitely
operating “on the line”; that is, in real time, or perhaps even looking
ahead by a certain amount so that it can not only keep up with
production but also predict forthcoming changes and make corrections in
time to be of use.

The human process controller is stuck with methods like those of the
cook who mixes up his recipe with a spoonful of this, and three pinches
of that, sniffs or tastes the batter subjectively, and may end up with a
masterpiece or a flop. Computer control processes the same batter
through the pipes at a thousand gallons a minute and catches
infinitesimal variations in time to correct them before the hotcakes are
baked. In effect it makes hindsight into foresight by compressing time
far more than man could hope to do.

Early applications of the computer in industrial processes were simply
those of data “loggers,” or monitors. It was still up to the human
operator to interpret what the computer observed and recorded, and to
throw the switch, close the valve, or push the panic button as the case
demanded. Actual computer control, the “closing of the loop” as the
engineers call it, is the logical next step. This replaces the human
operator, or at least relegates him to the role of monitor.

The Great Lakes hot-rolling steel mill has been mentioned as an example
of complete computer control. In Hayange, France, the first European
completely automated steel-beam mill is slated to go into operation late
in 1962. The Jones & Laughlin Steel Corporation in this country uses a
digital computer system to control continuous annealing in its
Aliquippa, Pennsylvania, plant, and is evaluating an RCA
computer-controlled tin-plating line operating at 3,000 feet a minute.
Newer computer-control applications in the offing include sintering and
other metal production operations.

[Illustration:

  _Minneapolis-Honeywell_

  Boston ice cream makers, H. P. Hood & Sons, use computer to make
    pushbutton ice cream. Analog computer thinks out recipes, punches
    them on cards to operate valves.
]

To those of us who consume it, ice cream may not seem a likely candidate
for computer control. However, the firm of H. P. Hood & Sons uses
computer control in its blending operation, finding it 20,000 times as
fast, and more accurate than when handled by human operators, since
computer controls hold mixes within one-tenth of 1 per cent accuracy.
Automation is a significant breakthrough in this industry, whose history
goes back 110 years, and in baking, which is a little older. The Sara
Lee bakeries use the computer too in assembling the ingredients for
their goodies. To bake such cakes, Mother will have to get herself a
computer.

Minneapolis-Honeywell furnished the computer for the ice-cream control;
this same company delivered a system for the Celanese Corporation of
America’s multimillion dollar acetyl manufacturing plant at Bay City,
Texas. The new plant produces a petrochemical used in plastics, paint,
synthetic rubber, dye, fibers, and other products. Going “on-stream” in
1962, the Celanese plant will produce half a billion pounds of chemicals
annually.

Russia has been mentioned as active in industrial computer control. A
case in point is the soda plant at Slavyansk in the Donets Basin, which
was recently test-operated for a continuous period of 48 hours by
computer. An unusual feature of this test was that the computer was in
Kiev, almost 400 miles away. A wire link between the two cities
permitted monitoring and control of the plant from Kiev in what the
Russians claim as the first remote automatic operation of such a plant.

Other Soviet achievements include two large-scale automatically
controlled installations. In oil-field operation at Tataria, gas and oil
outputs from many wells are monitored and controlled from a central
station, dropping the work force required from 600 to 100. The other
installation controls irrigation servicing 9,000 acres. A desktop
control handles the pumping of water from the Syr Darya River through
underground pipes, and distribution to Uzbekistan cotton fields. The
Russians have also designed an automatic distillation unit for the
Hungarians. With an annual capacity of a million tons, the unit was
installed in the large Szoeny refinery and scheduled for operation by
1962.

Refineries in the United States are also employing automatic controls in
their operations. Phillips Petroleum installed a digital computer
control system in its Sweeney, Texas, plant to achieve maximum
efficiency in its thermal cracking process. In the first step of an
experimental program, Phillips, working with Autonetics computer
engineers, used a digital computer to plan optimum furnace operation. An
initial 10 per cent improvement was achieved in this way, and a further
6 per cent gain resulted when a digital computer was installed on-line
to operate the cracking furnace.

The Standard Oil Company of California is using an IBM 7090 in San
Francisco to control its catalytic or “cat” cracking plant in El
Segundo, some 450 miles away. The need for computer speed and accuracy
is shown by the conditions under which the cracking plant must operate
continuously with no shutdowns except for repair. Each day, two million
gallons of petroleum is mixed in the cracker with the catalyst, a
metallic clay. The mixing takes place at incandescent heat of 1,000° F.,
and the resulting inferno faces operators with more than a hundred
changing factors to keep track of, a job feasible only with computer
help.

Another use of computer control in the petroleum industry is that of
automatic gasoline blending, as done by the Gulf Oil Corporation. A
completely electronic system is in operation at Santa Fe Springs,
California. The system automatically delivers the prescribed quantities
of gasoline for the desired blend. In case of error or malfunction of
equipment, the control alerts the human supervisor with warning lights
and an audible alarm. If he does not take proper action the control
system automatically shuts itself off.

From the time the war-inspired industry of synthetic rubber production
began in 1940 until very recently, it has been almost entirely a manual
operation. Then in 1961 Goodyear Tire & Rubber introduced computer
control into the process at its Plioflex plant in Houston, Texas.
Goodyear expects the new system to increase its “throughput” and also to
improve the quality of the product through tighter, smoother control of
the complicated operation. Other chemical processors using computer
control in their plants include Dow Chemical, DuPont, Monsanto, Union
Carbide, Sun Oil, and The Texas Company.

Adept at controlling the flow of material through pipes, the computer
can also control the flow of electricity through wires. An example of
this application is the use of digital computers in electric-utility
load-control stations. A typical installation is that of the
Philadelphia Electric Company in Philadelphia, the first to be
installed. Serving 3-1/2 million customers, the utility relies on a
Minneapolis-Honeywell computer to control automatically and continuously
the big turbine generators that supply electric power for the large
industrial area. The memory of the computer stores data about the
generators, transmission-line losses, operating costs, and so on.
Besides controlling the production of power for most economy, the
computer in its spare time performs billing operations for exchange of
power carried on with Pennsylvania-New Jersey-Maryland Interconnection
and Delaware Power & Light Company and Atlantic City Electric Company.

Other utilities using computer control are the Riverside Power Station
of the Gulf States Utilities Company, Southern California Edison, and
the Louisiana Power & Light Company’s Little Gypsy station in New
Orleans.

Another industry that makes use of a continuous flow of material is now
being fitted for computer control, and as a result papermakers may soon
have a better product to sell. IBM has delivered a 1710 computer to
Potlach Forests, Inc., in Idaho for control of a paperboard machine 500
feet long. Papermaking up to now has been more art than science because
of the difficulty of controlling recipes. With the computer, Potlach
expects to make better paper, have less reject material, and spend less
time in changing from one product run to another.

Showing that automatic control can work just about anywhere, the English
firm of Cliffe Hill Granite Company in Markfield, Leicestershire,
controls its grading and batching of granite aggregate from a central
location. Besides rock-crushers, cement plants like Riverside Cement
Company use computer control in the United States.

Thus far most of the computer control operations we have discussed are
in the continuous-processing fields of chemicals or other uniform
materials. The computer is making headway in the machine shop too,
although its work is less likely of notice there since the control panel
is less impressive than the large machine tool it is directing. Aptly
called APT, for Automatically Programmed Tools, the new technique is the
brainchild of M.I.T. engineer Douglas Ross. Automatic control eliminates
the need for drill jigs and other special setup tools and results in
cheaper, faster, and more accurate machine work.

[Illustration:

  _International Business Machines Corp._

  Controlled by instructions generated by IBM’s AUTOPROMPT, a Pratt &
    Whitney Numeric-Keller continuous-path milling machine shapes a raw
    aluminum block (upper left) into the saddle-shaped piece shown at
    right. The surface is a portion of a geometric shape called a
    hyperbolic paraboloid.
]

A coded tape, generated by a computer, controls the milling machine,
drill press, or shaper more accurately than the human machinist could.
In effect, the computer studies a blueprint and punches out instructions
on tape that tell the machine what it is to do, how much of it, and for
how long. Huge shaping and contouring machines munch chunks of metal
from blanks to form them into complex three-dimensional shapes.
Remington Rand UNIVAC and IBM are among the companies producing
computers for this purpose. The trend is to simpler, more flexible
control so that even small shops can avail themselves of the new
technique. In a typical example of the savings possible with “numerical”
tape control, these were the comparative costs:

[Illustration:

  _Control Engineering_

  Operation of computer-controlled freight yard in England.
]

                                _Conventional_      _Tape
                                             Control_

                   Tooling            $755        $45

                   Setup time      15 min.    15 min.

                   Work time       15 min.    11 min.

                   Cost per          $2.96      $1.81
                   part

Beyond the automated single- or multipurpose tool is the completely
computer-controlled assembly line. Complete automation of products like
automobiles may be some distance off, but there is nothing basically
unworkable about the idea. Simpler things will be made first, and to
promote thinking along these lines, Westinghouse set up an automatic
assembly line for paperweights. An operator typed the initials of
manufacturing department managers on a computer, which transferred the
instructions to a milling machine. The machine cut the initials in
aluminum blocks which were then automatically finished, painted, and
packaged for shipment as completed paperweights.

Another firm, Daystrom, Inc., is designing a computer control system for
assembly lines which will adjust itself for the “best” product as an
output. President Tom Jones described the principle in which the
computer will begin production, then move valves, switches, or other
controls a small amount. Measuring the finished product, it will decide
if the change is in the right direction, and proceed accordingly. Once
it finds the optimum point, it will lock in this position and settle
down to business.

An excellent example of the computerized assembly line is the Western
Electric Company carbon resistor production line at its Winston-Salem
plant. A digital computer with a 4,096-word memory is used for the
programming, setup, and feedback control of the eleven-station line. It
can accept a month’s scheduling requirements for deposited carbon
high-quality resistors in four power ratings and almost any desired
resistance values. Production rate is 1,200 units per hour.

The computer keeps track of the resistors as they are fabricated,
rejecting those out of specification and adjusting the process controls
as necessary. Operations include heating, deposition of carbon, contact
sputtering, welding, grooving, and inspecting.


                              _The Robots_

Most of these automated factory operations are doing men’s work, but it
is only when we see the robot in the shape of ourselves that cold chills
invade our spines. Children’s Christmas toys lately have included
mechanical men who stride or roll across the floor and speak, act, and
even “think” in more or less humanoid fashion, some of them hurling
weapons in a rather frightening manner. There is an industrial robot in
operation today which may recall the dread of Frankenstein, though its
most worried watchers are perhaps union officials. Called Unimate, this
factory worker has a single arm equipped with wrist and hand. It can
move horizontally through 220 degrees, and vertically for 60 degrees,
and extend its arm from 3 feet to 7 feet at the rate of 2-1/2 feet a
second. Without a stepladder, it can reach from the floor to a point
nearly 9 feet above it. Unimate can pick up 75 pounds, and its 4-inch
fingers can clamp together on an iron bar or a tool with a force of up
to 300 pounds.

The robot weighs close to a ton and a half, but can be moved from job to
job on a fork-lift truck. Its designers have turned up a hundred
different jobs that Unimate could do, including material loading,
packaging, welding, spray painting, assembly work, and so on. The robot
has a memory and can retain the 16,000 “bits” of information necessary
for 200 operations. To teach it a new task, it is only necessary to
“help” it manually through each step one time. Unimate can be instructed
to wait for an external signal during its task, such as the opening of a
press or a furnace door.

Advantages of a robot are many and obvious. Pretty girls passing by will
not distract it, nor will it require time for lunch or coffee breaks, or
trips to the washroom. If necessary it will work around the clock
without asking for double power for overtime. High temperatures, noxious
gases, flying sparks, or dangerous liquids will not be a severe hazard,
and Unimate never gets tired or forgets what it is doing.

But Unimate has some drawbacks that are just as obvious. It can’t tell
one color from another, and thus might paint parts the wrong color and
never know the difference. It is not readily movable, and not very
flexible either. It costs $25,000, and will need about $1,300 in
maintenance a year. Some industry spokesmen say that this is far too
much, and Unimate has a long way to go before it puts any people out of
work. Others say it is a step in the right direction, and this is
probably a fair evaluation.

Apparently United States Industries, Inc., whose AutoTutor teaching
machines are pacing the field, has made another step in the right
direction with its “TransfeRobot 200.” This mechanical assembly-line
worker is an “off-the-shelf” item, and currently in use by about fifty
manufacturers. TransfeRobot uses its own electronic brain, coupled with
a variety of magnetic, mechanical, or even pneumatic fingers to pick up,
position, insert, remove, and do other necessary operations on small
parts.

Besides these capabilities, TransfeRobot controls secondary operations
such as drilling, embossing, stamping, welding, and sealing. It is now
busy building things like clocks, typewriters, automobile steering
assemblies, and electrical parts. No one-job worker, it can be
re-programmed for other operations when a new product is needed, or
quickly switched to another assembly line if necessary. Billed as a new
hand for industry, TransfeRobot obviously has its foot in the door
already. United States Industries estimates current yearly sales of its
small automation equipment at about $3 million.

[Illustration:

  _Massachusetts Institute of Technology_

  Dr. Heinrich Ernst, Swiss graduate student at MIT, watches his
    computer-controlled “hand” pick up a block and drop it in the box.
]

The robots in Čapek’s play _R.U.R._ looked like their human makers, but
scientist Claude Shannon is more realistic. “These robots will probably
be something squarish and on wheels, so they can move around and not
hurt anybody and not get hurt themselves. They won’t look like the
tin-can mechanical men in comic strips. But you’ll want them about
man-size, so their hands will come out at table-top or assembly-line
level.” Since Professor Shannon is the man who sparked the
implementation of symbolic logic in computers, his ideas are not
crackpot, and the Massachusetts Institute of Technology’s Hand project
is a good start toward a real robot. Dr. Heinrich Ernst, a young Swiss,
developed Hand with help from Shannon. Controlled by a digital computer,
the hand moves about and exercises judgment as it encounters objects.
Such research will make true robots of the remotely manipulated machines
we have become familiar with in nuclear power experiments, underwater
exploration, and so forth. Hughes Aircraft’s “Mobot” is a good example,
and it is obvious that the robot’s bones, muscles, and nerves are
available. All they need is the brain to match.

While we wait fearfully for more robots which look the way we think
robots should, the machine quietly takes over controlling more and more
even bigger projects. The computer does a variety of tasks, from the
simple one of cutting rolling-mill stock into optimum lengths to
minimize waste, to that of running an electronic freight yard in which
cars are classified and made up automatically. The computer in this
application not only measures the car and weighs it, but also computes
its rollability. Using radar as its eyes, the computer gauges the speed
and distance between cars as they are being made up and regulates their
speed to prevent damaging bumps. To the chagrin of veteran human
switchmen, the computer system has proved it can “hump” cars—send them
coasting to a standing car for coupling—without the occasional
resounding crash caused by excessive speed.

About all that is holding up similarly automated subway trains in the
United States is approval from the union. Soviet Russia claims she
already has computer-run subways and even ships. The latter application
took place on the oil tanker _Engineer Pustoshkin_ plying the Caspian
Sea. The main complaint of the director of this research work, P.
Strumpe, is that ships are not yet designed for computer control and
will change for the better when their designers realize the error of
their ways.

[Illustration:

  _Hughes Aircraft Company_

  Mobot Mark II, carrying a Geiger counter in its “hands,” demonstrates
    how it can substitute for men in dangerously radiated areas.
]

Minneapolis-Honeywell in this country is working toward the complete
automation of buildings, pointing out that they are as much machines as
structures. A 33-story skyscraper in Houston will use a central computer
to check 400 points automatically and continuously. Temperature and
humidity will be monitored, as well as doors and windows. Presence of
smoke and fire will be automatically detected, and all mechanical
equipment will be monitored and controlled. Equipped with cost figures,
the central computer will literally “run” the building for optimum
efficiency and economy. Harvard University has a central control for
seventy-six campus buildings, and in Denver work is being done toward a
central control for a number of large buildings. It is fitting that
automation of buildings be carried on, since historically it was in the
home that self-control of machines was pioneered with automatic control
of furnaces with thermostats.

[Illustration:

  _Robodyne Division, U.S. Industries, Inc._

  TransfeRobot assembly-line worker installs clockwork parts with speed
    and precision.
]

In this country our traffic is crying for some kind of control, and New
York is already using punched-card programming to control part of the
city’s traffic. The Federal administration is studying a bold proposal
from RCA, Bendix, General Motors, and Westinghouse for an automatically
controlled highway. The reason? Traffic is getting to be too much for
the human brain to deal with. A better one has to be found, and the
computer is applying for the job.

The coming of automation has been likened to a tidal wave. It is useless
to shovel against it, and the job would seem to be to find suitable life
preservers to keep us afloat as it sweeps in over the world. One
approach is that of a nonprofit foundation to study the impact of
automation on workers. This group, a joint United States Industries,
Inc., and International Association of Machinists organization, has
already come up with a scheme for collecting “dues” from the machines,
in annual amounts of from $25 to $1,000, depending on the work output of
the machine.

A key project of the foundation is a study of effective retraining of
workers to fit them for jobs in the new, computerized factory. Such
studies may well have to be extended from the assembly line to the
white-collar worker and executive as well. The computer can wear many
different kinds of hats!


------------------------------------------------------------------------


         Teaching Machine Age
    Lilyn E. Carlton in _Saturday Review_

    “_In the good old-fashioned school days,
     Days of the golden rule,
     Teacher said, ‘Good morning, class,’
     And so she started school._

     _Alas! How different things are now,
     The school day can’t begin
     Till someone finds the socket
     And plugs the teacher in._”




                       10: The Academic Computer


     It was inevitable that the computer invade, or perhaps “infiltrate”
is the better word, our education system. Mark I and ENIAC were
university-born and -bred, and early research work was done by many
institutions using computers. A logical development was to teach formal
courses in using the computer. While application of the machine in
mathematical and scientific work came first, its application to business
and to the training of executives for such use of the computer was soon
recognized. As an example, one of two computers installed by U.C.L.A. in
1957 was for use exclusively in training engineering executives as well
as undergraduates in engineering economy.

Early courses were aimed at those already in industry, in an attempt to
catch them up with the technology of computer-oriented systems in
business and science. As special courses, many of these carried a high
tuition fee. Next came the teaching of professors and deans of
engineering institutions in techniques of computer education for
undergraduates. Today the computer is being taught to many students in
many schools. New York University has a $3 million computer at its
Courant Institute of Mathematical Sciences, being used by students in
basic and applied research on projects ranging from the design of
bridges to the analysis of voting patterns in Congress.

M.I.T. recently added a digital computer to teach its students the
operation of electronic data-processing equipment. Another computer is
used in more sophisticated work including speech analysis, study of
bioelectrical signals, and the simulation of automata as in the “Hand”
project. At the computing center of the University of Michigan a second
generation of computers is being installed. Students in some one hundred
different courses use these computers, programming them with a language
developed at the University and called MAD, for Michigan Algorithm
Decoder. These are typical examples of perhaps two hundred schools using
computers.

That knowledge of computer techniques is essential for the engineering
graduate is evident in the fact that of a recent class of such students
at Purdue, 1,600 used the computer during the term. Less known is the
integration of computer courses in secondary education. The Royal McBee
Corporation teaches a special course on the computer to youngsters at
Staples High in Westport, Connecticut. At the end of the first four-week
session it was found that the students, fifteen to seventeen years old,
had learned faster than adults. At New York’s St. Vincent Ferrer
Catholic High School, 400 girls participated in a similar project
conducted by Royal McBee. Other high schools are following suit, and
computers are expected to appear in significant numbers in high schools
before the end of 1962. Textbooks on computers, written for high-school
students, are available. As an example of the ability of young people in
this field, David Malin of Walter Johnson High School in Rockville,
Maryland, read his own paper on the use of computers to simulate human
thought processes to science experts attending the 1961 Eastern Joint
Computer Conference held in Washington, D.C.

The use of the computer in the classroom encompasses not only colleges
and high schools, but extends even to prisons. Twenty inmates of a
Pennsylvania state institution attended a pilot program teaching
computer techniques with a UNIVAC machine.

[Illustration:

  _Datamation_

  Seventeen-year-old David Malin who presented a paper on computers at
    the Eastern Joint Computer Conference in 1961.
]

The United States is not alone in placing importance on the computer in
schools. Our Department of Commerce has published details of Russian
work in this direction, noting that it began in 1955 and places high
priority on the training of specialists in computer research, machine
translation, automation, and so on. The Department of Commerce feels
that these courses, taught at the graduate, undergraduate, and even
high-school level, are of high quality.


                          _Teaching Machines_

Thus far we have talked of the computer only as a tool to be studied and
not as an aid to learning in itself. In just a few years, however, the
“teaching machine” has become familiar in the press and controversial
from a number of standpoints, including those of being a “dehumanizer”
of the process of teaching and a threat to the apple business!

Actually, the computer has functioned for some time outside the
classroom as a teaching machine. Early applications of analog computers
as flight simulators were true “teaching machines” although perhaps the
act was not as obvious as classroom use of a computer to teach the three
R’s. Even today, there are those who insist that such use of the
computer by the military or industry offers more potential than an
academic teaching machine. Assembly workers have been taught by
programmed audiovisual machines such as Hughes Aircraft’s Videosonic
trainer, and the government has taught many technicians by computer
techniques. A shrewd observer, however, noting that the computer is
called stupid, bluntly points out that any untaught student is in the
same category, and that perhaps it takes one to teach one.

A strong motivation for looking to the machine as a public teaching tool
is the desperation occasioned by the growing shortage of teachers. If
the teaching machine could take over even some of the more simple chores
of the classroom, early advocates said, it would be worth the effort.

Formal study of machine methods of teaching have a history of forty
years or more. In the 20’s, Sydney Pressey designed and built automatic
teaching—or more precisely, testing—machines at Ohio State University.
These were simply multiple-choice questions so mechanized as to be
answered by the push of a button rather than with a pencil mark. A right
answer advanced the machine to the next question, while an error
required the student to try again. Pressey wisely realized the value in
his machines; the student could proceed at his own pace, and his
learning was also stimulated by immediate recognition of achievement. To
further enforce this learning, some of the teaching machines dispensed
candy for a correct answer. Using this criterion, it would seem that
brighter students could be recognized by their weight.

Unfortunately, Pressey’s teaching machines did not make a very big
splash in the academic world, because of a combination of factors. The
machines themselves had limitations in that they did not present
material to be learned but were more of the nature of _a posteriori_
testing devices. Too, educators were loath to adopt the mechanized
teachers for a variety of reasons, including skepticism, inertia,
economics, and others. However, machine scoring of multiple-choice tests
marked with special current-conducting pencils became commonplace.

Another researcher, B. F. Skinner, commenced work on a different kind of
teaching machine thirty years ago at Harvard. Basically his method
consists of giving the subject small bits—not computer “bits,” but the
coincidence is interesting—of learning at a time, and reinforcing these
bits strongly and immediately. Skinner insists that actual “recall” of
information is more important than multiple-choice “recognition,” and he
asks for an answer rather than a choice. Called “operant reinforcement,”
the technique has been used not only on man, but on apes, monkeys, rats,
dogs, and surprisingly, pigeons.

During World War II, Dr. Skinner conducted “Project Pigeon” for the
military. In this unusual training program, the feathered students were
taught to peck at certain targets in return for which they received food
as a reward. This combination of apt pupils and advanced teaching
methods produced pigeons who could play ping-pong. This was in the early
days of missile guidance, and the pigeons next went into training as a
homing system for these new weapons! To make guidance more reliable, not
one but three pigeons were to be carried in the nose of the device.
Lenses in the missile projected an image before each pigeon, who
dutifully pecked at his “target.” If the target was in the center of the
cross hairs, the missile would continue on its course; if off to one
side, the pecking would actuate corrective maneuvers. As Project
“Orcon,” for Organic Control, this work was carried on for some time
after the end of the war. Fortunately for the birds, however, more
sophisticated, inorganic guidance systems were developed.

The implications of the pigeon studies in time led to a new teaching
method for human beings. Shortly after Skinner released a paper on his
work in operant reinforcement with the pigeons, many workers in the
teaching field began to move in this direction. For several years
Skinner and James Holland have been using machines of this type to teach
some sections of a course in human behavior to students at Radcliffe and
Harvard. Rheem Califone manufactures the DIDAK machine to Skinner’s
specifications.

To the reasons advanced by those who see teacher shortages looming,
Skinner adds the argument that a machine can often teach better. Too
much time, he feels, has been spent on details that are not basic to the
problem. Better salaries for teachers, more teachers, and more schools
do not in themselves improve the actual teaching. Operant reinforcement,
Skinner contends, _does_ get at the root of the problem and, in addition
to relieving the teacher of a heavy burden, the teaching machine
achieves better results in some phases of teaching. It also solves
another problem that plagues the educator today. It is well known that
not all of us can learn at the same rate. Since it is economically and
culturally impossible except in rare cases to teach children in groups
of equal ability, a compromise speed must be established. This is fine
for the “average” child, of whom there may actually be none in the
classroom; it penalizes the fast student, and the slow student perhaps
even more. The teaching machine, its proponents feel, takes care of this
difficulty and lets each proceed at his own rate. Since speed in itself
is no sure indicator of intelligence, the slow child, left to learn as
he can, may reach heights not before dreamed possible for him.

Many educators agree that automated teaching is past due. James D. Finn,
Professor of Education at the University of Southern California,
deplores the lack of modern technology in teaching. “Technology during
the period from 1900 to 1950 only washed lightly on the shores of
instruction,” he says. “The cake of custom proved to be too tough and
the mass production state, at least 100 years behind industry, was not
entered except here and there on little isolated islands.”

[Illustration:

  _Educational Science Division,_

  _U.S. Industries, Inc._

  AutoTutor teaching machine has programs for teaching many subjects.
]

These little isolated islands are now getting bigger and closer
together. The Air Force has for some time trained technicians at Keesler
Field with U.S. Industries AutoTutor machines, and also uses them at the
Wright Air Development Center. The Post Office Department has purchased
fifty-five U.S. Industries’ Digiflex trainers. Following this lead,
public education is beginning to use teaching machines. San Francisco
has an electronic computer version that not only teaches, tests, and
coaches, but even sounds an alarm if the student tries to “goof off” on
any of the problems. The designers of the machine selected a sure-fire
intellectual acronym, PLATO, for Programmed Logic for Automatic Teaching
Operations. The System Development Corporation, the operations firm that
designed the SAGE computer, calls its computer-controlled classroom
teacher simply CLASS. This machine uses a Bendix G-15 computer to teach
twenty youngsters at a time.

To show the awareness of the publishers of texts and other educational
material, firms like Book of Knowledge, Encyclopedia Britannica Films,
and TMI Grolier are in the “teaching machine” business, and the
McGraw-Hill Book Company and Thompson Ramo Wooldridge, Inc., have teamed
to produce computerized teaching machines and the programs for them.
Other publishers using “programming” techniques in their books include
Harcourt-Brace with its 2600 series (for 2,600 programmed steps the
student must negotiate), Prentice-Hall, and D. C. Heath. Entirely new
firms like Learning, Incorporated, are now producing “programs” on many
subjects for teaching machines.

Subjects available in teaching machine form include algebra,
mathematics, trigonometry, slide rule fundamentals, electronics,
calculus, analytical geometry, plane geometry, probability theory,
electricity, Russian, German, Spanish, Hebrew, spelling, music
fundamentals, management science, and even Goren’s bridge for beginners.

While many of these teaching machines are simply textbooks programmed
for faster learning, the conversion of such material into
computer-handled presentation is merely one of economics. For example, a
Doubleday TutorText book costs only a few dollars; an automatic
AutoTutor Mark II costs $1,250 because of its complex searching facility
that requires several thousand branching responses. However, the
AutoTutor is faster and more effective and will operate twenty-four
hours a day if necessary. With sufficient demand the machine may be the
cheaper in the long run.

The System Development Corporation feels that its general concept of
automated group education will be feasible in the near future despite
the high cost of advanced electronic digital computers. It cites pilot
studies being conducted by the State of California on data-processing
for a number of schools through a central facility. Using this same
approach, a single central computer could serve several schools with
auxiliary lower-priced equipment. Even a moderately large computer used
in this way could teach a thousand or more students simultaneously and
_individually_, the Corporation feels. After school hours, the computer
can handle administrative tasks.

[Illustration:

  _System Development Corp._

  The CLASS facility incorporates an administrative area, hallway,
    combined observation and counseling area, and a large classroom area
    divided by a folding wall.
]

In the CLASS system developed by the System Development Corporation, the
“branching” concept is used. In a typical lesson program, if the student
immediately answers that America was discovered by Christopher Columbus,
he will be told he is correct and will then be branched to the next
item. If he answers Leif Ericson, the computer takes time out to
enlighten the pupil on that score. Next, it reinforces the correct date
in the student’s mind before asking another question. Although it would
seem that a lucky student could progress through the programmed lesson
on guesswork alone, the inexorable laws of probability rule this out. He
cannot complete the lesson until he has soaked up all the information it
is intended to impart. He can do this without an error, in a very short
time, or he can learn by the trial-and-error process, whichever is
better suited to his speed and mental ability.

Making up the program for the teaching machine is a difficult task and
requires the services of technical expert, psychologist, and programmer.
An English-like language is used in preparing a CLASS program for the
computer. Put on magnetic tape, the program goes into the memory of the
computer and is called out by proper responses from the student as he
progresses through the lesson.

[Illustration:

  _System Development Corp._

  Students in CLASS are learning French in a group mode of automated
    instruction.
]

Complex as the programming is, entries from the student’s control are
processed into the computer in about one-tenth of a second, and an
answer is flashed back in about the same amount of time. Remember that
the CLASS computer is handling twenty students at a time, and that in
addition to teaching it is keeping a complete record of how the student
fared at each step of the lesson.

It is obvious that the binary or yes-no logic of the computer ties in
with the concept put forth by Skinner and others of presenting small
bits of information at a time. We can use the game of 20 Questions as a
good analogy. Even getting only simple yes-no answers, skilled players
can elicit an amazing amount of information in often far less than the
permitted number of questions. Thus even complex subjects can be broken
down into simple questions answerable by discrete choices from the
student.

The automated group education system of the System Development
Corporation is made up of the following components: a digital computer
to control and select the material presented and to analyze responses, a
magnetic tape storage unit, a typewriter for printing out data analysis,
a slide projector and screen for presenting educational materials, and
individual desks with keyboards for the students’ responses.

We have pointed out that even though it is possible to break down
educational material into multiple-choice or yes-no answers to which are
assigned intrinsic values, the ideal system permits answers on a linear
scale. In other words, instead of picking what he considers the most
nearly correct, a student writes his own answer. Some experts feel that
the advances being made in optical scanning, or “reading” techniques for
computers, will result in linear programming of the teaching machines
within the next ten years. Such a development will do much to alleviate
the complaint that the machine exerts a rigid mechanizing effect on the
teaching process.

While fear of displacement motivates some teachers to distrust the
machine, an honest belief that the human touch is necessary in the
schoolroom is also a large factor against acceptance. Yet these same
wary teachers generally use flash cards, flip charts, and other
mechanical aids with no qualms. The electronic computer is a logical
extension of audiovisual techniques, and in time the teacher will come
to accept it for what it is.

The human teacher will continue to be an indispensable element in
education, but he must recognize that as our technology becomes more
complex he will need more and more help. In 1960 there were about 44
million students in our classrooms, and about 135,000 too few teachers.
By 1965 it is estimated there will be 48 million students and 250,000
teachers fewer than we need. Parallel with this development is the
rapidly growing need for college graduates. One large industrial firm
which employs 150,000 hires only 300 college graduates a year at
present, but will need 7,000 when it automates its plants. The pressure
of need thus is forcing our educational system to make use of the most
efficient means of educating our students.

Beyond simply taking its place with other aids, however, the computer
will make great changes in our basic concepts of teaching, according to
Dr. Skinner. He asks the question “Are the students who learn in spite
of a confusing presentation of a subject better for the experience, or
were they better students at the outset?” He advances this argument to
say that perhaps “easy” learning is actually the best; that we would do
well to analyze the behavior called thinking and then produce it
according to these specifications. The traditional teacher finds the
prospect alarming and questions the soundness of minimizing failure and
maximizing success.

There is not yet definite agreement by other psychologists with
Skinner’s contention that recall rather than recognition is the desired
method. Neither is it sure that the negative reinforcement of a number
of incorrect choices may result in remembering wrong answers. And of
course the division between rote learning and creativity is an important
consideration. The answers may well lie in the computer, which when
properly programmed is about the most logical device we have available
to us. Thus the machine may determine the best teaching methods and then
use them to teach us. Regardless of these as yet unanswered questions,
however, the future of the teaching machine seems to be assured. One
authority has predicted that it will be a $100 million market by 1965.

An intriguing use of computer techniques in teaching is being
investigated by Corrigan Communications, which scores students answering
questions on telecourses. This work is being done with a course in
medicine, and with the rapid growth of educational television the
implications of combining it and teaching machine techniques are of
great importance.

Classroom teaching is not the only educational application for the
teaching machine. A computer-controlled library is an interesting
thought, with the patron requesting information from a central computer
and having it presented instantaneously on a viewing screen in front of
him. Such a system could conceivably have access to a national library
hookup, constantly updated with new material. Such a service would also
be available for use during school study hall, or by the teacher during
class.

Visitors to the World’s Fair in Seattle previewed the computerized
information center of the future. Called Library 21, it is considered a
prototype of the next century’s core libraries which will be linked to
smaller branches by communications networks. Many computers were
displayed, tied in with teaching machines, language laboratories, and
information from the Great Books, tailored to the individual
questioner’s sex, personality, and mental level. Also shown was a photo
process that reduces a 400-page book to the size of a postage stamp for
storage.

With this kind of progress, we can in the foreseeable future request and
receive up-to-date information of any kind of human knowledge
anywhere—in language we can understand. Another computer application
sure to come is that of handling correspondence courses. The teaching of
extension courses in the home, through television and some sort of
response link, has been mentioned, and it is not impossible that the
school as a physical plant may one day no longer be necessary.

[Illustration:

  _International Business Machines Corp._

  This system supplies legal information in minutes, with insertion of
    punched-card query (top). Using inquiry words, computer prints
    citations of statutes (middle); then, on request, full text (below).
]

Since the computer itself does not “teach,” but merely acts as a
go-between for the man who prepared the lesson or program and the
student who learns, it would seem that some of our teachers may become
programmers. The System Development Corporation has broken the teaching
machine program into three phases: experimenting with the effects of
many variables on teaching machine effectiveness, developing a
simplified teaching machine, and finally, analyzing the educational
system to find where and how the machine fits. Research is still in the
first phase, that of experiment. But it is known that some programs
produced so far show better results than conventional teaching methods,
and also that teaching machines can teach any subject involving factual
information. Thus it is evident they will be useful in schools and also
in industry and military training programs.


                               _Language_

If man is to use the computer to teach himself, he must be able to
converse with it. In the early days of computers it was said with a good
deal of justification that the machine was not only stupid but decidedly
insular as well. In other words, man spoke to it in its own language or
not at all. A host of different languages, or “compilers” as they are
often called, were constructed and their originators beat the drums for
them. With tongues like ALGY, ALGOL, COBOL, FACT, FLOWMATIC, FORTRAN,
INTERCOM, IT, JOVIAL, LOGLAN, MAD, PICE, and PROLAN, to name a few, the
computer has become a tower of Babel, and a programmer’s talents must
include linguistics.

One language called ALGOL, for Algorithmic Oriented Language, had pretty
smooth sailing, since it consists of algebraic and arithmetic notation.
Out of the welter of business languages a compromise Common Business
Oriented Language, or COBOL, evolved. What COBOL does for programming
computer problems is best shown by comparing it with instructions once
given the machine. The sample below is typical of early machine
language:

[Illustration:

  SUBTRACT QUANTITY-SOLD FROM BALANCE-ON-HAND. IF BALANCE-ON-HAND IS NOT
    LESS THAN REORDER-LEVEL THEN GO TO BALANCE-OK ELSE COMPUTE
    QUANTITY-TO-BUY = TOTAL-SALES-3-MOS/3.
]

Recommended by a task force for the Department of Defense, industry, and
other branches of the government, COBOL nevertheless has had a tough
fight for acceptance, and there is still argument and confusion on the
language scene. New tongues continue to proliferate, some given birth by
ALGOL and COBOL themselves. Examples of this generation are GECOM,
BALGOL, and TABSOL. One worthy attempt at a sort of machine Esperanto is
called a pun-inviting UNCOL, for Universal Computer-Oriented Language
and seems to be a try for the computer’s vote. One harried
machine-language user has suggested formation of an “ALGOLICS Anonymous”
group for others of his ilk, while another partisan accuses his
colleagues in Arizona of creating a new language while “maddened by the
scent of saguaro blossoms.”

It was recently stated that perhaps by the time a decision is ultimately
reached as to which will be the general language, there will be no need
of it because by then the computer will have learned to read and write,
and perhaps to listen and to speak as well. Recent developments bear out
the contention.

Although it has used intermediate techniques, the computer has proved it
can do a lot with our language in some of the tasks it has been given.
Among these is the preparation of a Bible concordance, listing principal
words, frequency of appearance, and where they are found. The computer
tackled the same job on the poems of Matthew Arnold. For this chore,
Professor Stephen Maxfield Parrish of Cornell worked with three
colleagues and two technicians to program an IBM 704 data-processing
system. In addition to compiling the list of more than 10,000 words used
most often by Arnold, the computer arranged them alphabetically and also
compiled an appendix listing the number of times each word appeared. To
complete the job, the computer itself printed the 965-page volume. The
Dead Sea Scrolls and the works of St. Thomas Aquinas have also been
turned over to the computer for preparation of analytical indexes and
concordances.

At Columbia University, graduate student James McDonough gave an IBM 650
the job of sleuthing the author of _The Iliad_ and _The Odyssey_. Since
the computer can detect metric-pattern differences otherwise practically
undiscoverable, McDonough felt that the machine could prove if Homer had
written both poems, or if he had help on either. Thus far he is sure the
entire _Iliad_ is the work of one man, after computer analysis of its
112,000 words. The project is part of his doctoral thesis. A recent
article in a technical journal used a title suggested by an RCA 501, and
suspicion is strong that the machines themselves are guilty of burning
midnight kilowatts to produce the acronyms that abound in the industry.
The computer is even beginning to prove its worth as an abstracter.

Other literary jobs the computer has done include the production of a
book of fares for the International Air Transport Association. The
computer compiled and then printed out this 420-page book which gives
shortest operating distances between 1,600 cities of the world. Now
newspapers are beginning to use computers to do the work of typesetting.
These excursions into the written language of human beings, plus its
experience as a poet and in translation from language to language, have
undoubtedly brought the computer a long way from its former
provincialism.

As pointed out, computer work with human language generally is not
accomplished without intermediate steps. For example, in one of the
concordances mentioned, although the computer required only an hour to
breeze through the work, a programmer had spent weeks putting it in the
proper shape. What is needed is a converter which will do the work
directly, and this is exactly what firms like Digitronics supply to the
industry. This computer-age Berlitz school has produced converters for
Merrill Lynch, Pierce, Fenner & Smith for use in billing its
stock-market customers, Wear-Ever as an order-taking machine, _Reader’s
Digest_ for mailing-list work, and Schering Corporation for rat-reaction
studies in drug research, to mention a few.

The importance of such converters is obvious. Prior to their use it was
necessary to type English manually into the correct code, a costly and
time-consuming business. Converters are not cheap, of course, but they
operate so rapidly that they pay for themselves in short order. Merrill
Lynch’s machine cost $120,000, but paid back two-thirds of that amount
in savings the first year. There is another important implication in
converter operation. It can get computer language out of English—or
Japanese, or even Swahili if the need arises. A more recent Digitronics’
converter handles information in English or Japanese.

If the computer has its language problems, man has them also, to the
_n_th degree. There are about 3,000 tongues in use today; mercifully,
scientific reports are published in only about 35 of these. Even so, at
least half the treatises published in the world cannot be read by half
the world’s scientists. Unfortunately, UNESCO estimates that while 50
per cent of Russian scientists read English, less than 1 per cent of
United States scientists return the compliment! The ramifications of
these facts we will take up a little later on; for now it will be
sufficient to consider the language barrier not only to science but also
to culture and the international exchange of good will that can lead to
and preserve peace. Esperanto, Io, and other tongues have been tried as
common languages. One recent comer to the scientific scene is called
Interlingua and seems to have considerable merit. It is used in
international medical congresses, with text totaling 300,000 words in
the proceedings of one of these. But a truly universal language is, like
prosperity, always just around the corner. Even the scientific
community, recognizing the many benefits that would accrue, can no more
adopt Interlingua or another than it can settle on the metric system of
measurement. Our integration problems are not those of race, color, and
creed only.

Before Sputnik our interest in foreign technical literature was not as
keen as it has been since. One immediate result of the satellite
launching by the Russians was amendment of U.S. Public Law 480 to permit
money from the sale of American farm equipment abroad to be used for
translation of foreign technical literature. We are vitally concerned
with Russia, but have also arranged for thousands of pages of scientific
literature from Poland, Yugoslavia, and Israel. Communist China is
beginning to produce scientific reports too, and Japanese capability in
such fields as electronics is evident in the fact that the revolutionary
“tunnel diode” was invented by Esaki in Japan.

It is understandable that we should be concerned with the output of
Russian literature, and much attention has been given to the
Russian-English translator developed by IBM for the Air Force. It is
estimated that the Russians publish a billion words a year, and that
about one-third of this output is technical in nature. Conventional
translating techniques, in addition to being tedious for the
translators, are hopelessly slow, retrieving only about 80 million words
a year. Thus we are falling behind twelve years each year! Outside of a
moratorium on writing, the only solution is faster translation.

The Air Force translator was a phenomenal achievement. Based on a
photoscopic memory—a glass disc 10 inches in diameter capable of storing
55,000 words of Russian-English dictionary in binary code—the system
used a “one-to-one” method of translation. The result initially was a
translation at the rate of about 40 words per minute of Russian into an
often terribly scrambled and confusing English. The speed was limited
not by the memory or the computer itself but by the input, which had to
be prepared on tape by a typist. Subsequently a scanning system capable
of 2,400 words a minute upped the speed considerably.

Impressive as the translator was, its impact was dulled after a short
time when it was found that a second “translation” was required of the
resulting pidgin English, particularly when the content was highly
technical. As a result, work is being done on more sophisticated
translation techniques. Making use of predictive analysis, and “lexical
buffers” which store all the words in a sentence for syntactical
analysis before final printout, scientists have improved the translation
a great deal. In effect, the computer studies the structure of the
sentence, determining whether modifiers belong with subject or object,
and checking for the most probable grammatical form of each word as
indicated by other words in the sentence.

The advanced nature of this method of translation requires the help of
linguistics experts. Among these is Dr. Sydney Lamb of the University of
California at Berkeley who is developing a computer program for analysis
of the structure of any language. One early result of this study was the
realization that not enough is actually known of language structure and
that we must backtrack and build a foundation before proceeding with
computer translation techniques. Dr. Lamb’s procedure is to feed English
text into the computer and let it search for situations in which a
certain word tends to be preceded or followed by other words or groups
of words. The machine then tries to produce the grammatical structure,
not necessarily correctly. The researcher must help the machine by
giving it millions of words to analyze contextually.

What the computer is doing in hours is reproducing the evolution of
language and grammar that not only took place over thousands of years,
but is subject to emotion, faulty logic, and other inaccuracies as well.
Also working on the translation problem are the National Bureau of
Standards, the Army’s Office of Research and Development, and others.
The Army expects to have a computer analysis in 1962 that will handle 95
per cent of the sentences likely to be encountered in translating
Russian into English, and to examine foreign technical literature at
least as far as the abstract stage.

Difficult as the task seems, workers in the field are optimistic and
feel that it will be feasible to translate all languages, even the
Oriental, which seem to present the greatest syntactical barriers. An
indication of success is the announcement by Machine Translations Inc.
of a new technique making possible contextual translation at the rate of
60,000 words an hour, a rate challenging the ability of even someone
coached in speed-reading! The remaining problem, that of doing the
actual reading and evaluation after translation, has been brought up.
This considerable task too may be solved by the computer. The machines
have already displayed a limited ability to perform the task of
abstracting, thus eliminating at the outset much material not relevant
to the task at hand. Another bonus the computer may give us is the ideal
international and technical language for composing reports and papers in
the first place. A logical question that comes up in the discussion of
printed language translation is that of another kind of translation,
from verbal input to print, or vice versa. And finally from verbal
Russian to verbal English. The speed limitation here, of course, is
human ability to accept a verbal input or to deliver an output. Within
this framework, however, the computer is ready to demonstrate its great
capability.

A recent article in _Scientific American_ asks in its first sentence if
a computer can think. The answer to this old chestnut, the authors say,
is certainly yes. They then proceed to show that having passed this test
the computer must now learn to perceive, if it is to be considered a
truly intelligent machine. A computer that can read for itself, rather
than requiring human help, would seem to be perceptive and thus qualify
as intelligent.

Even early computers such as adding machines printed out their answers.
All the designers have to do is reverse this process so that printed
human language is also the machine’s input. One of the first successful
implementations of a printed input was the use of magnetic ink
characters in the Magnetic Ink Character Recognition (MICR) system
developed by General Electric. This technique called for the printing of
information on checks with special magnetic inks. Processed through
high-speed “readers,” the ink characters cause electrical currents the
computer can interpret and translate into binary digits.

Close on the heels of the magnetic ink readers came those that use the
principle of optical scanning, analogous to the method man uses in
reading. This breakthrough came in 1961, and was effected by several
different firms, such as Farrington Electronics, National Cash Register,
Philco, and others, including firms in Canada and England. We read a
page of printed or written material with such ease that we do not
realize the complex way our brains perform this miracle, and the optical
scanner that “reads” for the computer requires a fantastically advanced
technology.

As the material to be read comes into the field of the scanner, it is
illuminated so that its image is distinct enough for the optical system
to pick up and project onto a disc spinning at 10,000 revolutions per
minute. In the disc are tiny slits which pass a certain amount of the
reflected light onto a fixed plate containing more slits. Light which
succeeds in getting through this second series of slits activates a
photoelectric cell which converts the light into proportionate
electrical impulses. Because the scanned material is moving linearly and
the rotating disc is moving transversely to this motion, the character
is scanned in two directions for recognition. Operating with great
precision and speed, the scanner reads at the rate of 240 characters a
second.

National Cash Register claims a potential reading rate for its scanner
of 11,000 characters per second, a value not reached in practice only
because of the difficulty of mechanically handling documents at this
speed. Used in post-office mail sorting, billing, and other similar
reading operations, optical scanners generally show a perfect score for
accuracy. Badly printed characters are rejected, to be deciphered by a
human supervisor.

It is the optical scanner that increased the speed of the
Russian-English translating computer from 40 to 2,400 words per minute.
In post-office work, the Farrington scanner sorts mail at better than
9,000 pieces an hour, rejecting all handwritten addresses. Since most
mail—85 per cent, the Post Office Department estimates—is typed or
printed, the electronic sorter relieves human sorters of most of their
task. Mail is automatically routed to proper bins or chutes as fast as
it is read.

The electronic readers have not been without their problems. A drug firm
in England had so much difficulty with one that it returned it to the
manufacturer. We have mentioned the one that was confused by Christmas
seals it took for foreign postage stamps. And as yet it is difficult for
most machines to read anything but printed material.

An attempt to develop a machine with a more general reading ability, one
which recognizes not only material in which exact criteria are met, but
even rough approximations, uses the _gestalt_ or all-at-once pattern
principle. Using a dilating circular scanning method, the “line drawing
pattern recognizer” may make it possible to read characters of varying
sizes, handwritten material, and material not necessarily oriented in a
certain direction. A developmental model recognizes geometric figures
regardless of size or rotation and can count the number of objects in
its scope. Such experimental work incidentally yields much information
on just how the eye and brain perform the deceptively simply tasks of
recognition. Once 1970 had been thought a target date for machine
recognition of handwritten material, but researchers at Bell Telephone
Laboratories have already announced such a device that reads cursive
human writing with an accuracy of 90 per cent.

The computer, a backward child, learned to write long before it could
read and does so at rates incomprehensible to those of us who type at
the blinding speed of 50 to 60 words a minute. A character-generator
called VIDIAC comes close to keeping up with the brain of a high-speed
digital computer and has a potential speed of 250,000 characters, or
about 50,000 words, per _second_. It does this, incidentally, by means
of good old binary, 1-0 technique. To add to its virtuosity, it has a
repertoire of some 300 characters. Researchers elsewhere are working on
the problems to be met in a machine for reading and printing out
1,000,000 characters per second!

None of us can talk or listen at much over 250 words a minute, even
though we may convince ourselves we read several thousand words in that
period of time. A simple test of ability to hear is to play a record or
tape at double speed or faster. Our brains just won’t take it. For
high-speed applications, then, verbalized input or output for computers
is interesting in theory only. However, there are occasions when it
would be nice to talk to the computer and have it talk back.

In the early, difficult days of computer development, say when Babbage
was working on his analytical engine, the designer probably often spoke
to his machine. He would have been stunned to hear a response, of
course, but today such a thing is becoming commonplace. IBM has a
computer called “Shoebox,” a term both descriptive of size and
refreshing in that is not formed of initial capitals from an ad writer’s
blurb. You can speak figures to Shoebox, tell it what you want done with
them, and it gets busy. This is admittedly a baby computer, and it has a
vocabulary of just 16 words. But it takes only 31 transistors to achieve
that vocabulary, and jumping the number of transistors to a mere 2,000
would increase its word count to 1,000, which is the number required for
Basic English.

The Russians are working in the field of speech recognition too, as are
the Japanese. The latter are developing an ambitious machine which will
not only accept voice instructions, but also answer in kind. To make a
true speech synthetizer, the Japanese think they will need a computer
about 5,000 times as fast as any present-day type, so for a while it
would seem that we will struggle along with “canned” words appropriately
selected from tape memory.

We have mentioned the use of such a tape voice in the computerized
ground-controlled-approach landing system for aircraft, and the airline
reservation system called Unicall in which a central computer answers a
dialed request for space in less than three seconds—not with flashing
lights or a printed message but in a loud clear voice. It must pain the
computer to answer at the snail-like human speed of 150 words a minute,
so it salves its conscience by handling 2,100 inputs without getting
flustered.

The writer’s dream, a typewriter that has a microphone instead of keys
and clacks away merrily while you talk into it, is a dream no longer.
Scientists at Japan’s Kyoto University have developed a computer that
does just this. An early experimental model could handle a hundred
Japanese monosyllables, but once the breakthrough was made, the Japanese
quickly pushed the design to the point where the “Sonotype” can handle
any language. At the same time, Bell Telephone Laboratories works on the
problem from the other end and has come up with a system for a
typewriter that talks. Not far behind these exotic uses of digital
computer techniques are such things as automatic translation of
telephone or other conversations.


                        _Information Retrieval_

It has been estimated that some 445 trillion words are spoken in each
16-hour day by the world’s inhabitants, making ours a noisy planet
indeed. To bear out the “noisy” connotation, someone else has reckoned
that only about 1 per cent of the sounds we make are real information.
The rest are extraneous, incidentally telling us the sex of the speaker,
whether or not he has a cold, the state of his upper plate, and so on.
It is perhaps a blessing that most of these trillions of words vanish
almost as soon as they are spoken. The printed word, however, isn’t so
transient; it not only hangs around, but also piles up as well. The pile
is ever deeper, technical writings alone being enough to fill seven
24-volume encyclopedias each day, according to one source. As with our
speech, perhaps only 1 per cent of this outpouring of print is of real
importance, but this does not necessarily make what some have called the
Information Explosion any less difficult to cope with.

The letters IR once stood for infra-red; but in the last year or so they
have been appropriated by the words “information retrieval,” one of the
biggest bugaboos on the scientific horizon. It amounts to saving
ourselves from drowning in the fallout from typewriters all over the
earth. There are those cool heads who decry the pushing of the panic
button, professing to see no exponential increase in literature, but a
steady 8 per cent or so each year. The button-pushers see it
differently, and they can document a pretty strong case. The technical
community is suffering an embarrassment of riches in the publications
field.

While a doubling in the output of technical literature has taken the
last twelve years or so, the next such increase is expected in half that
time. Perhaps the strongest indication that IR is a big problem is the
obvious fact that nobody really knows just how much has been, is being,
or will be written. For instance, one authority claims technical
material is being amassed at the rate of 2,000 pages a minute, which
would result in far more than the seven sets of encyclopedias mentioned
earlier. No one seems to know for sure how many technical journals there
are in the world; it can be “pinpointed” somewhere between 50,000 and
100,000. Selecting one set of figures at random, we learn that in 1960
alone 1,300,000 different technical articles were published in 60,000
journals. Of course there were also 60,000 books on technical subjects,
plus many thousands of technical reports that did not make the formal
journals, but still might contain the vital bit of information without
which a breakthrough will be put off, or a war lost. Our research
expenses in the United States ran about $13 billion in 1960, and the
guess is they will more than double by 1970. An important part of
research should be done in the library, of course, lest our scientist
spend his life re-inventing the wheel, as the saying goes.

To back up this saying are specific examples. For instance, a scientific
project costing $250,000 was completed a few days before an engineer
came across practically the identical work in a report in the library.
This was a Russian report incidentally, titled “The Application of
Boolean Matrix Algebra to the Analysis and Synthesis of Relay Contact
Networks.” In another, happier case, information retrieval saved Esso
Research & Engineering Co. a month of work and many thousands of dollars
when an alert—or lucky—literature searcher came across a Swedish
scientist’s monograph detailing Esso’s proposed exploration. Another
literature search obviated tests of more than a hundred chemical
compounds. Unfortunately not all researchers do or can search the
literature in all cases. There is even a tongue-in-cheek law which
governs this phenomenon—“Mooer’s” Law states, “An information system
will tend not to be used whenever it is more painful for a customer to
have information than for him not to have it.”

As a result, it has been said that if a research project costs less than
$100,000 it is cheaper to go ahead with it than to conduct a rigorous
search of the literature. Tongue in cheek or not, this state of affairs
points up the need for a usable information retrieval system. _Fortune_
magazine reports that 10 per cent of research and development expense
could be saved by such a system, and 10 per cent in 1960, remember,
would have amounted to $1.3 billion. Thus the prediction that IR will be
a $100 million business in 1965 does not seem out of line.

The Center for Documentation at Western Reserve University spends about
$6-1/2 simply in acquiring and storing a single article in its files. In
1958 it could search only thirty abstracts of these articles in an hour
and realized that more speed was vital if the Center was to be of value.
As a result, a GE 225 computer IR system was substituted. Now
researchers go through the entire store of literature—about 50,000
documents in 1960—in thirty-five minutes, answering up to fifty
questions for “customers.”

[Illustration:

  _International Business Machines Corp._

  The document file of this WALNUT information retrieval system contains
    the equivalent of 3,000 books. A punched-card inquiry system locates
    the desired filmstrip for viewing or photographic reproduction.
]

[Illustration:

  _International Business Machines Corp._

  This image converter of the WALNUT system optically reduces and
    transfers microfilm to filmstrips for storage. Each strip contains
    99 document images. As a document image is transferred from
    microfilm to filmstrip, the image converter simultaneously assigns
    image file addresses and punches these addresses into punched cards
    controlling the conversion process.
]

The key to information retrieval lies in efficient abstracting. It has
been customary to let people do this task in the past because there was
no other way of getting it done. Unfortunately, man does not do a
completely objective job of either preparing or using the abstract, and
the result is a two-ended guessing game that wastes time and loses facts
in the process. A machine abstracting system, devised by H. Peter Luhn
of IBM, picks the words that appear most often and uses them as keys to
reduce articles to usable, concise abstracts. A satisfactory solution
seems near and will be a big step toward a completely computerized IR
system.

For several years there has been a running battle between the computer
IR enthusiast and the die-hard “librarian” type who claims that
information retrieval is not amenable to anything but the human touch.
It is true that adapting the computer to the task of information
retrieval did not prove as simple as was hoped. But detractors are in
much the same fix as the man with a shovel trying to build a dike
against an angry rising sea, who scoffs at the scoop-shovel operator
having trouble starting his engine. The wise thing to do is drop the
shovel and help the machine. There will be a marriage of both types of
retrieval, but Verner Clapp, president of the Washington, D.C., Council
on Library Resources, stated at an IR symposium that computers offer the
best chance of keeping up with the flood of information.

One sophisticated approach to IR uses symbolic logic, the forte of the
digital computer. In a typical _reductio ad logic_, the following
request for information:

An article in English concerning aircraft or spacecraft, written neither
before 1937 or after 1957; should deal with laboratory tests leading to
conclusions on an adhesive used to bond metal to rubber or plastic; the
adhesive must not become brittle with age, must not absorb plasticizer
from the rubber adherent, and must have a peel-strength of 20 lbs/in; it
must have at least one of these properties—no appreciable solution in
fuel and no absorption of solvent.

becomes the logical statement:

KKaVbcPdeCfg, and KAhiKKKNjNklSmn.

Armed with this symbolic abbreviation, the computer can dig quickly into
its memory file and come up with the sought-for article or articles.

It has been suggested that the abstracting technique be applied at the
opposite end of the cycle with a vengeance amounting to birth control of
new articles. A Lockheed Electronics engineer proposes a technical
library that not only accepts new material, but also rejects any that is
_not_ new. Here, of course, we may be skirting danger of the type risked
by human birth control exponents—that of unwittingly depriving the world
of a president, or a powerful scientific finding. Perhaps the screening,
the function of “garbage disposal,” as one blunt worker puts it, should
be left as an after-the-fact measure.

Despite early setbacks, the computer is making progress in the job of
information retrieval. Figures of a 300 per cent improvement in
efficiency in this new application are cited over the last several
years. Operation HAYSTAQ, a Patent Office project in the chemical patent
section accounting for one-fifth of all patents, showed a 50 per cent
improvement in search speed and 100 per cent in accuracy as a result of
using automated methods. Desk-size computer systems with solid-state
circuits are being offered for information retrieval.

The number of scientific information centers in this country, starting
with one in 1830, reached 59 in 1940 and now stands at 144.
Significantly, of 2,000 scientists and engineers working at these
centers, 381 are computer people.

Some representative information retrieval applications making good use
of computer techniques are the selection of the seven astronauts for the
Mercury Project from thousands of jet pilots, Procter & Gamble’s
Technical Information Service, demonstration of an electronic law
library to the American Bar Association, and Food Machinery and Chemical
Corporation’s Central Research Laboratory. The National Science
Foundation, the National Bureau of Standards, and the U.S. Patent Office
are among the government agencies in addition to the military services
that are interested in electronic information retrieval.


                               _Summary_

The impact of the computer on education, language and communication, and
the handling of information is obviously already strongly felt. These
inroads will be increased, and progress hastened in the years ahead of
us. Perhaps of the greatest importance is the assigning to the machine
functions closer to the roots of all these things. Rather than simply
read or translate language, for example, the computer seems destined to
improve on it. The same applies to the process of teaching and to the
storage and retrieval of data. The electronic computer has shown that it
is not a passive piece of equipment, but active and dynamic in nature.
It will soon be as much a part of the classroom and library as books;
one day it may take the place of books themselves.

[Illustration:

  Lichty, © _Field Enterprises, Inc._

  “How come they spend over a million on our new school, Miss Finch, and
    then forget to put in computer machines?”
]


------------------------------------------------------------------------

“_’Tis one and the same Nature that rolls on her course, and whoever has
sufficiently considered the present state of things might certainly
conclude as to both the future and the past._”

                    —Montaigne




                           11: The Road Ahead


In Book One of _Les Miserables_, Cosette says, “Would you realize what
Revolution is, call it Progress; and would you realize what Progress is,
call it Tomorrow.” Victor Hugo’s definitions apply well to what has been
termed by some the computer revolution and by others simply the natural
evolution of species. The computer has a past and a present,
differentiated mainly by the slope of the line plotting progress against
time. Its future, which blurs somewhat with the present, will obviously
be characterized by a line approaching the vertical.

The intelligent machine has been postulated for years, first by the
scientist, then by the science-fiction writer, and now again by the
scientist. Norbert Wiener of cybernetics fame, Ashby and his homeostat,
Grey Walter and his mechanical turtles, A. M. Turing, John von Neumann,
and others, have recently been joined by men like Ramo, Samuel, Newell,
_et al._, who, if not actually beating the drums for machine
intelligence, do more than admit to the possibility. For each such pro
there are cons, of course, from sincere, intelligent authorities who in
effect holler “Get a horse!” at those who say the computer is coming.

The Royal Society in England met its stiffest opposition from otherwise
intelligent people who deplored naturalism in any form. Perhaps such
detractors are a necessary goad, a part of progress. At any rate,
science survived the Nicholas Gimcrack jibes of the Popes and Addisons
and Swifts. Darwin was more right than Butler, though the latter
probably made more money from his work. Today, we find a parallel
situation in that there are those who refuse to accept the computer as
an intelligent machine, though it is interesting to watch these
objectors regroup and draw another line the machine dare not go past.

The writers of science and pseudo-science have often been accused of
fantasy and blue-sky dreams. A case in point in the electronics field is
the so-called “journalistor” or marvelous successor to the transistor.
Such riding off in all directions with each new laboratory experiment
may be justified in that it prods the scientist who must keep up with
the press and his advertising department! This theory apparently works,
and now it seems that the most startling and fantastic stories come not
from writers, but from the scientists themselves.

In 1960 the Western Joint Computer Conference was held in San Francisco,
and one session was devoted to the fanciful design and use of a computer
with the problem-solving capability of an intelligent man and the speed
and capacity of a high-speed data-processor. It was proposed to use
“tunnel-effect tetrodes” with a switching time of one ten-billionth of a
second as the logic and storage elements. These would be fabricated of
thin-film materials by electron beam micromachining, and 100 billion of
them could be packed into a cubic inch volume. With these tiny
components and new circuit modes a supercomputer could be built, stored
with information, and programmed to solve what one of the participants
called the most difficult problem the human being faces today—that of
bargaining.

This computer has not yet been built; it won’t be for some time. But
design and fabrication are moving in that direction on a number of
fronts. One of these fronts is that of hardware, the components used in
building up the computer circuitry. In a decade we moved from vacuum
tubes to transistors to thin-film devices. Examples of shrinkage on a
gross scale are shown in the use of a single ferrite core to replace
some twenty conventional (relatively speaking!) components.

Memory circuits once were mechanical relays or tube circuits. Briefly
they were transistorized, and then ferrite cores. Magnetic thin-film
circuits have now been developed, making random-access storage almost as
compact as the sequential tape reel. As circuits grow smaller the major
problem is manipulating them, or even seeing them, and a sneeze can be
disastrous in today’s electronics plant.

One early journalistor was the molecular circuit. Many scientists and
engineers working in the field scoffed at or derided such a visionary
scheme. But the industry has indeed progressed into the
integrated-circuit technology—a sort of halfway point—and is now on the
fringe of actual functional block techniques in which the individual
components are not discernible. Electronic switching and other action at
the molecular level is close to reality, and hardheaded scientists now
speak calmly of using a homogeneous block of material as a memory,
scanning its three dimensions with the speed of light to locate any one
or more of billions of bits of data in a few inches of volume.

Writing on the head of a pin was a prophetic bit of showmanship, and
pinhead-size computers will not necessarily have pinhead mentalities.
This progress toward a seemingly hopeless goal takes on an inexorable
quality when the writings of von Neumann are compared with the state of
the art today. Starting out much faster but much larger than similar
elements of the brain, computer components have been made even faster
while simultaneously shrinking dramatically toward the dimensions
necessary to produce quantitative equivalence. It happens that these
goals work out well together, the one helping the other. Circuitry is
now at the point where speed is ultimately dependent on that limiter of
all physical activity, the speed of light, or of electrons through a
conductor. Only by putting elements closer together can speed be
increased; thus one quality is not achieved at the sacrifice of the
other.

[Illustration:

  _International Business Machines Corp._

  This experimental “memory plane” consists of 135 cryotron devices
    built up in a 19-layer “sandwich.” Produced automatically, it is an
    example of continued shrinking of computer elements.
]

As an example of the progress being made toward speeding up computers,
speakers at the recent Winter General Meeting of the American Institute
of Electrical Engineers described a coming generation of “gigacycle”
computers now on the drawing boards. Present electronic machines operate
at speeds in the megacycle range, with 50 million cycles per second
representing the most advanced state of the art. Giga means billion;
thus the new round of computers will be some thousand times as fast as
those now operating.

Among the firms who plan such ultraspeed computers are RCA, IBM, and
Sperry Rand Corporation. To achieve such a great increase in speed
requires faster electronic switches. Transistors have been improved, and
more exotic devices such as tunnel diodes, thin-film cryotrons, magnetic
thin-films, parametrons, and traveling-wave tubes are now coming into
use. Much of the development work is being supported by the U.S. Bureau
of Ships. Operational gigacycle computers are expected within two years!

Not just the brickmaker, but the architect too has been busy in the job
of optimizing the computer. The science of bionics and the study of
symbolic logic lead to better ways of doing things. The computer itself
comes up with improvements for its next generation, making one part do
the work of five, and eliminating the need for whole sections of
circuitry. Most computers have a fixed “clock”; that is, they operate at
a certain cyclic rate. Now appearing on the scene are “asynchronous”
computers which don’t stand around waiting when one job is done, as
their predecessors did.

One advanced notion is the “growing” of complex electronic circuitry, in
which a completed amplifier, or array of amplifiers, is pulled from the
crystal furnace much the way material for transistors is now grown.
Pooh-poohed at first as ridiculous, the notion has been tried
experimentally. Since a computer is basically a multiplicity of simple
units, the idea is not far off at that. It is conceivable that crystal
structure can be exploited to produce millions of molecules of the
proper material properly aligned for the desired electronic action.

With this shrinking come the benefits of small size, low power
consumption, low cost, and perhaps lower maintenance. The computer will
be cheap enough for applications not now economically feasible. As this
happens, what will the computer do for us tomorrow?

A figure of 7 per cent is estimated for the amount of paperwork the
computer has taken over in the business world. Computer men are eyeing a
market some five times that amount. It does not take a vivid imagination
to decide that such a percentage is perhaps conservative in the extreme.
Computer sales themselves promise to show a fourfold increase in the
five-year period from 1960 to 1965, and in the past predictions have
been exceeded many times.

As population grows and business expands in physical size and
complexity, it is obvious that the computer and its data-processing
ability will be called upon more and more. There is another factor, that
of the internationalizing of business. Despite temporary setbacks of
war, protective tariffs, insular tendencies, and the like, in the long
run we will live in one integrated world shrunk by data links that can
get information from here to there and back again so fast it will be
like conversing with someone across the room. Already planners are
talking worldwide computerized systems.

As a mathematical whiz, the computer will relieve us of our money
worries. Coupled with the credit card, perhaps issued to us at birth, a
central computer will permit us to make purchases anywhere in the world
and to credit our account with wages and other income. If we try to
overdraw, it may even flash a warning light as fast as we put the card
in the slot! This project interests General Dynamics researchers.

Of more importance than merely doing bookkeeping is the impact the
computer will have on the planning and running of businesses. Although
it is found in surveys that every person thinks computer application
reaches to the level just below his in the management structure, pure
logic should ultimately win out over man’s emotional frailties at all
levels. Operations research, implemented by the computer, will make for
more efficient businesses. Decisions will increasingly be made not by
vice-presidents but by digital computers. At first we will have to
gather the necessary information for these electronic oracles, but in
time they will take over this function themselves.

Business is tied closely to education, and we have had a hint of the
place the computer will make for itself in education. The effect on our
motivation to learn of the little need for much learning will be
interesting. But then, is modern man a weaker being because he kills a
tiger with a high-powered rifle instead of club or bare hands—or has no
need to kill the tiger in the first place?

After having proved itself as a patent searcher, the computer is sure to
excel as inventor. It will invade the artistic field; computers have
already produced pleasing patterns of light. Music has felt the effect
of the computer; the trend will continue. Some day not far off the hi-fi
enthusiast will turn on his set and hear original compositions one after
the other, turned out by the computer in as regular or random form as
the hearer chooses to set the controls. Each composition will bring the
thrill of a new, fresh experience, unless we choose to go back in the
computer’s memory for the old music.

The computer will do far more in the home than dream up random music for
listening pleasure. The recorded telephone answerer will give way to one
that can speak for us, making appointments and so on, and remembering to
bring us up to date when we get home. A small computer to plug in the
wall may do other things like selecting menus and making food purchases
for next week, planning our vacations, and helping the youngsters with
their homework. It is even suggested that the computer may provide us
with child-guidance help, plus psychological counsel for ourselves and
medical diagnoses for the entire family. The entire house might be
computerized, able to run itself without human help—even after people
are gone, as in the grimly prophetic story by Ray Bradbury in which a
neat self-controlled home is shown as the curtains part in the morning.
A mechanical sweeper runs about gathering up dust, the air conditioning,
lighting, and entertainment are automatic, all oblivious to the fact
that one side of the house is blackened from the blast of a bomb.

Perhaps guarding against that eventuality is the most important job the
computer can do. Applications of computing power to government have been
given; and hints made of the sure path from simple tasks like the census
and income tax, Peace Corps work, and so on to decision-making for the
president. Just as logic is put to work in optimizing business, it can
be used to plan and run a taut ship of state. At first such an
electronic cabinet member will be given all available information, which
it will evaluate so as to be ready to make suggestions on policy or
emergency action. There is more reason for it going beyond this status
to become an active agent, than there is against. Government has already
become so complex that perhaps a human brain, or a collection of them,
cannot be depended on to make the best possible decision. As
communications and transportation are speeded up, the problem is
compounded. Where once a commander-in-chief could weigh the situation
for days before he had to commit himself and his country to a final
choice, he may now be called upon to make such a far-reaching decision
in minutes—perhaps minutes from the time he is awakened from a sound
sleep. The strongest opposition to this delegation of power is man’s own
vanity. No machine can govern, even if it can think, the politician
exclaims. The soldier once felt the same way; but operations research
has given him more confidence in the machine, and SAGE and NORAD prove
to him that survival depends on the speed and accuracy of the electronic
computer.

Incurable romanticism is found even among our scientific community. The
National Bureau of Standards describes a computer called ADAM, for
Absolutely Divine Automatic Machine. But the scientists also know that
ADAM, or man, needs help. Rather than consider the machine a tool, or
even an extension of man’s mind, some are now concerned with a kind of
marriage of man and machine in which each plays a significant part. Dr.
Simon Ramo, executive vice president of Thompson Ramo Wooldridge, Inc.,
has termed this mating of the minds “intellectronics.” The key to this
combination of man’s intellect and that of electronics is closer rapport
between the team members.

[Illustration:

  _Department of Defense_

  Computer use in defense is typified in this BIRDIE system of the
    United States Army.
]

The man-machine concept has grown into a science called, for the present
at least, “synnoetics,” a coinage from the Greek words _syn_ and _noe_
meaning “perceive” and “together.” This science is defined as the
treating of the properties of composite systems, consisting of
configurations of persons, mechanisms, plant or animal organisms, and
automata, whose main attribute is that their ability to invent, to
create, and to reason—their mental power—is greater than the mental
power of their components.

We get a not-too-fanciful look into the future in a paper by Dr. Louis
Fein presented in the summer 1961 issue of _American Scientist_, titled
“Computer-related Sciences (Synnoetics) at a University in 1975.” Dr.
Fein is an authority on computers, as builder of RAYDAC in 1952, and as
founder and president of the Computer Control Company. The paper
ostensibly is being given to alumni some years hence by the university
president. Dr. Fein tells us that students in the Department of
Synnoetics study the formal languages used in communication between the
elements of a synnoetic system, operations research, game theory,
information storage, organization and retrieval, and automatic
programming. One important study is that of error, called Hamartiology,
from the Greek word meaning “to miss the mark.”

The speaker tells us that this field was variously called cybernetics,
information science, and finally computer-related science before being
formally changed to the present synnoetics. A list of the courses
available to undergraduates includes:

Von Neumann Machines and Turing Machines

Elements of Automatic Programming

Theory, Design, and Construction of Compilers

Algorithms: Theory, Design, and Applications

Foundations of the Science of Models

The Theory, Design, and Application of Non-Numeric Models

Heuristics

Self-Programming Computers

Advice Giving—Man to Machine and Machine to Man

Simulation: Principles and Techniques

Pattern Recognition and Learning by Automata

  The Grammar, Syntax, and Use of Formal Languages for Communication
    Between Machine and Machine and Between Man and Man

  Man-Automaton Systems: Their Organization, Use, and Control

  Problem-Solving: an Analysis of the Relationship Between the
    Problem-Solver, the Problem, and the Means for Solution

  Measurements of the Fundamental Characteristics of the Elements of
    Synnoetic Systems


Of course, synnoetics spills over into the other schools, as shown in
the following typical courses taught:


                           Botany Department
                   Machine-Guided Taxonomy in Botany

                            Business School
                    Synnoetic “Business Executives”

                           Engineering School
               Theory of Error and Equipment Reliability
                 Design of Analog and Digital Computers

                         Humanities Department
             Theory of Creative Processes in the Fine Arts

                               Law School
             Patent and Precedence Searches with Computers
     The Effect of Automata on the Legislative and Judicial Process

                         Mathematics Department
         The Theory of Graphs and the Organization of Automata

                             Medical School
    Computer-Aided Medical Diagnosis and Prescription for Treatment

                               Philosophy
  The Relationships between Models and the Phenomena That Are Modeled

                         Psychology Department
        Studies in Intuition and Intellect of Synnoetic Systems
                 Simulation in the Behavioral Sciences

                          Sociology Department
                      Synnoetics in Modern Society

The speaker proudly refers to the achievement of the faculty mediator
and a computer in settling the “famous” strike of 1970.

He simply got both sides first to agree that each would benefit by
concentrating attention—not on arguing and finally settling the issues
one at a time—but on arguing and finally settling on a program for an
automaton. This program would evaluate the thousands of alternative
settlements and would recommend a small class of settlements each of
which was nearly optimum for both sides. The automaton took only 30
minutes to produce the new contract last year. It would have taken one
year to do this manually, and even then it would have been done less
exhaustively. Agreeing on the program took one week. Of course, you have
already heard that in many areas where people are bargaining or trying
to make optimum decisions such as in the World Nations Organization, in
the World Court, and in local, federal, and world legislative bodies,
there is now serious consideration being given to convincing opposing
factions to try to agree on a program and having once agreed on it, the
contract or legislation or judgment or decision produced with the
program would be accepted as optimum for both sides. Automata may also
be provided to judges and juries to advise them of the effects of such
factors as weight of evidence on verdicts in civil cases.

Dr. Fein makes an excellent case for the usefulness of the science of
synnoetics; the main point of challenge to his paper might be that its
date is too conservatively distant. Of interest to us here is the idea
of man and machine working in harmony for the good of both.

Another paper, “The Coming Technological Society,” presented by Dr.
Simon Ramo at the University of California at Los Angeles, May 1, 1961,
also discusses the possible results of man-machine cooperation during
the remainder of the twentieth century. He lists more than a dozen
specific and important applications for intellectronics in the decades
immediately ahead of us. Law, medicine, engineering, libraries, money,
and banking are among these. Pointing out that man is as unsuited for
“putting little marks on pieces of paper” as he was for building
pyramids with his own muscles, he suggests that our thumbprints and
electronic scanners will take care of all accounting. Tongue in cheek,
he does say that there will continue to be risks associated with life;
for instance, a transistor burning out in Kansas City may accidentally
wipe out someone’s fortune in Philadelphia.

The making of reservations is onerous busywork man should not have to
waste his valuable time on, and the control of moving things too is
better left to the machine for the different reason that man’s unaided
brain cannot cope with complex and high-speed traffic arteries, be they
in space or on Los Angeles freeways. Business and military management
will continue to be aided by the electronic machine.

But beyond all these benefits are those more important ones to our
brains, our society, and culture. Teaching machines, says Dr. Ramo, can
make education ten times more effective, thus increasing our intellect.
And this improved intellect, multiplied by the electronic machine into
intellectronic brainpower, is the secret of success in the world ahead.
Instead of an automated, robotlike regimented world that some predict,
Ramo sees greater democracy resulting. Using the thumbprint again, and
the speed of electronics, government of our country will be truly by the
people as they make their feelings known daily if necessary.

Intellectronic legislation will extend beyond a single country’s
boundaries in international cooperation. It will smash the language and
communication barriers. It will permit and implement not only global
prediction of weather, but global control as well. Because of the rapid
handling of vast amounts of information, man can form more accurate and
more logical concepts that will lead to better relations throughout the
world. Summing up, Dr. Ramo points out that intellectronics benefits not
only the technical man but social man as well:

The real bottleneck to progress, to a safe, orderly, and happy
transition to the coming technological age, lies in the severe disparity
between scientific and sociological advance. Having discussed
technology, with emphasis on the future extension of man’s intellect, we
should ask: Will intellectronics aid in removing the imbalance? Will
technology, properly used, make possible a correction of the very
imbalance which causes technology to be in the lead? I believe that the
challenging intellectual task of accelerating social progress is for the
human mind and not his less intellectual partner. But perhaps there is
hope. If the machines do more of the routine, everyday, intellectual
tasks and insure the success of the material operation of the world,
man’s work will be elevated to the higher mental domains. He will have
the time, the intellectual stature, and hence the inclination to solve
the world’s social problems. We must believe he has the capability.

[Illustration:

  _Thompson Ramo Wooldridge, Inc._

  Information in many forms can be displayed with “polymorphic”
    data-processing systems.
]

Antedating synnoetics and intellectronics is another idea of such a
relationship. In his book _The World, The Flesh and the Devil_, J. D.
Bernal considers man’s replacement of various of his body’s parts with
mechanical substitutes until the only organic remains would be his
brain. This is a sort of wrong-end-to synnoetics, but in 1929 when the
book was published there was already plenty of raw material for such a
notion. Wooden legs and hooks or claws for hands, metal plates for bone
material, for example; and the artificial heart already being developed.
More recently we have seen the artificial kidney used, along with other
organs. We have also added electronic gear to our organic components,
for example the “pacemaker” implanted in many laggard hearts to keep
them beating in proper cadence, plastic plumbing, and the like. There is
a word for this sort of part-organic, part-mechanical man: the name
“cyborg” for cybernetic organism was proposed by two New York doctors.
Their technical definition of cyborg is “an exogenously extended
organizational complex functioning as a homeostatic system.” There is of
course strong precedent in nature for the idea of such a beneficial
combination: symbiosis, the co-existence or close union of two
dissimilar organisms. The shark and his buddy, the pilot fish, are
examples; as are man and the many parasites to which he is host.

The idea of man being part of machine harks back to youthful rides in
soapbox racers, and later experiences driving cars or flying aircraft.
The pilot who flew “by the seat of his pants” in the early days easily
felt himself part of the machine. As planes—and cars—grew bigger and
more complex, this “one-manship” became more remote and harder to
identify. The jet transport pilot may well have the feeling of handling
a train when he applies force to his controls and must wait for it to be
amplified through a servo system and finally act on the air stream. In
the space age the man-machine combination not only survives but also
flourishes. Arthur C. Clarke writes in a science-fiction story of a
legless space man who serves well and happily in the weightlessness of
his orbiting satellite station.

We have two stages of development, then, not necessarily sequential: man
working with the machine and man as part of the machine. Several writers
have suggested a third stage in which the machine gradually supplants
the weaker human being much as other forms eased out the dinosaur of
old. William O. Stapledon’s book, _Last and First Men_, describes
immortal and literal giant brains. Many writers believe that these
“brains” will not be man’s, but those of the machine, since frail
humanity cannot survive in its increasingly hostile environment.

Arthur C. Clarke is most articulate in describing what he calls the
evolutionary cycle from man to machine. As the discovery of tools by
pre-man created man, so man’s invention of thinking machines set about
the workings that will make _him_ extinct. Clarke theorizes that this
breakthrough by man may well be his last, and that his machines will
“think” him off the face of the earth!

[Illustration:

  _Hughes Aircraft Company_

  Withstanding underwater pressures, at depths too great for human
    divers, a Mobot vehicle demonstrates in this artist’s concept how it
    can perform salvage and rescue operations at the bottom of the
    ocean.
]

As we move into a technology that embraces communication at a distance
of millions of miles, survival under death-dealing radiation, and travel
at fantastic speeds, man’s natural equipment falters and he must rely on
the machine both as muscle and brain. Intelligence arose from life but
does not necessarily need life, in the sense we think of it, to
continue. Thus the extension of man’s intellect by electronics as hailed
by Dr. Ramo will lead ultimately to our extinction.

Clarke feels that the man-machine partnership we have entered, while
mutually benevolent, is doomed to instability and that man with his
human shortcomings will fall by the wayside, perhaps in space, which may
well be the machine’s true medium. What will remain will be the
intelligent machine, reduced as time goes on to “pure” intelligence free
to roam where it will and do what it wants, a matterless state of
affairs that even Clarke modestly disclaims the imagination to speculate
upon.

Before writing man off as a lost cause, we should investigate a strong
argument against such a take-over by the machine. Man stands apart from
other creatures in his consciousness of himself. He alone seems to have
the ability to ponder his fate, to reflect, and to write books about his
thoughts and dreams. Lesser animals apparently take what comes, do what
they have to do, and get through this life with a minimum of changing
their environment and themselves. Thus far the machines man has built do
not seem to be conscious of themselves. While “rational beings,”
perhaps, they do not have the “ability to laugh” or otherwise show
conscious awareness of their fate. A term applied to primitive
mechanical beings is “plugsuckers.” They learn to seek out a wall socket
or other form of energy and nourish themselves much as animals must do.
Just where man himself switched from plugsucking and began to rewire his
own world is a fuzzy demarcation, but he seems to have accomplished
this.

Consciousness is subjective in the extreme, and thus far only in fiction
have computers paused to reflect and consider what they have done and
its effect on them. However, the machine-builder, if not yet the machine
itself, is aware of this consciousness problem. The Hoffman Electronics
Corporation recently published an advertisement in the form of a
science-fiction story by A. E. Van Vogt. The hero is a defense vehicle,
patrolling the Pacific more effectively because it thinks it is king of
the Philippine Deep. Its name is Itself, and it has a built-in alter
ego. Hoffman admits it has not produced a real Itself—yet, but points
out calmly that the company’s business _is_ the conversion of scientific
fiction to scientific fact.

It has been suggested that mechanical consciousness may evolve when the
computer begins to reproduce itself, a startling conception blessed in
theory by logicians and mathematicians, as well as philosophers. A crude
self-replicating model has been built by scientists—a toy train that
reproduces itself by coupling together the proper cars to copy the
parent train, a whimsical reflection of Samuel Butler’s baby engines
playing about the roundhouse door.

Self-reproducing machines may depend on a basic “cell” containing a
blueprint of what it should look like when complete, which simply hunts
around for the proper parts and assembles itself. In the process it may
even make an improvement or two. Having finished, it will make a carbon
copy of its blueprint and start another “baby” machine on the way.
Writers on this subject—some under the guise of science-fiction—wonder
at what point the _machines_ will begin to wonder about how _they_ came
to be. Will they produce philosophic or religious literature, or will
this step in evolution prove that consciousness was a bad mutation, like
seven fingers or three heads, and drop it from the list of instructions?

Clarke admits that the take-over by the machines is centuries off;
meantime we can enjoy a golden age of intellectronic partnership with
the machine. Linus Pauling, pointing out that knowledge of molecular
structure has taken away the mystery of life, hopes that a “molecular
theory of thinking” will be developed and so improve man that he may
remake his thoughts and his world. Mathematician John Williams believes
that existing human intelligence can preserve its distinction only by
withdrawing from competition with the machine and defining human
intelligence rigorously enough to exclude that of the machines. He
suggests using the computer not just for a molecular theory of thinking,
but also in the science of genetics to _design_ our children!

Whatever lies ahead, it seems obvious that one of the most important
things the computer can help us think about is the computer itself. It
is a big part of our future.


------------------------------------------------------------------------




                                 Index


 Abacus, 5, 21, 22, 60, 85, 129, 178, 181

 Abstracting computer, 245, 248

 Accuracy
   analog computer, 82
   digital computer, 87

 Ackerman, 110

 ADAM computer, 258

 Adaptive principle, 205

 Adders, 107, 108, 115

 Adding machine, 129

 Addition, computer, 106

 Address, computer, 63

 Advertising, use of computer, 180

 AID, 183, 184

 AIEE, 254

 Aiken, 46

 Air Force, 6, 132, 133, 151, 160, 182, 225

 Airborne computer, 90, 154, 158, 162

 AiResearch Mfg. Co., 69

 Airline reservations, computer, 58, 183, 184

 Algebra, Boolean, 8, 110, 119

 Alpha rhythm, 126

 Alphanumeric code, 104

 American Premium Systems, Inc., 175

 Analog computer, 21, 45, 72, 74, 80, 125, 203
   direct, 76, 79
   direct-current, 76
   discrete, 80
   indirect, 76, 79
   mechanical differential analyzer, 76
   scaling, 76

 Analytical engine, 36, 37

 AND gate, 112, 113, 117, 119

 Antikythera computer, 25

 Apollo computer, 182
   space vehicle, 169

 Applications, digital computer, 92

 _A priori_ concept, 126, 135

 APT computer, 209

 Aquinas, St. Thomas, 235

 Arabic numbers, 23

 Archytas, 25

 Arithmetic unit, computer, 51, 60

 Aristotle, 26

 Aristotelian logic, 109

 _Arizona Journal_, 179

 Army, U. S., 21, 78, 146, 259

 _Ars Magna_, 28, 29

 ARTOC, 157

 Artron, 136

 Ashby, W. Ross, 51, 124, 128, 251

 ASC computer, 155

 Associated Press computer system, 177

 Asynchronous computer, 255

 Athena computer, 52

 Atlas missile, 4, 168

 Atlas-Centaur missile, 169

 Atomic Energy Commission, U. S., 149

 Automatic
   control, 80, 203
   pilot, 203

 Automation, 26, 80, 173, 181, 201, 202, 203, 211, 217

 Automaton, 26

 Auto-parking, use of computer, 178

 Autonetics, 207

 AUTOPROMPT computer, 210

 AUTOTAG, 156

 AutoTutor teaching machine, 213, 225


 B-29, 45, 77, 82

 Babbage, 5, 35, 37, 41, 51

 Babylonian arithmetic, 23

 Ballistic computer, 83

 Banking, 1, 172, 173

 Bar Association, American, 152, 249

 Battelle Memorial Institute, 195

 Batten, Barton, Durstine, & Osborn, 180

 Bell Telephone Laboratories, 4, 147, 241

 Bendix Corp., 182, 190, 218

 Bendix G-15 computer, 183, 188

 Bernal, J. D., 264

 Bernstein, Alex, 141

 Bettelheim, Bruno, 144

 BIAX memory units, 10

 Bierce, Ambrose, 43, 121

 BINAC computer, 7, 47

 Binary, 98
   digit, 55, 104
   notation, 101, 103
   pure, 102, 104
   system, 85, 97, 99
   variables, 114

 Bionics, 7, 132, 135, 255

 BIRDIE, 259

 Birds, counting, 18

 Bit, 55, 104

 “Black box” concept, 50, 115

 BLADES system, 191

 Block diagram, 58

 BMEWS, 159

 Boeing Airplane Co., 186

 Boltzmann equation, 158

 Bomarc missile, 186

 _Book of Contemplation_, 27

 Book of Knowledge, 6, 226

 Boole, George, 38, 110

 Boolean algebra, 38, 110, 119

 Bradbury, Ray, 153, 257

 _Brain_, 121

 Brain
   computer, 128, 129, 130
   human, 87, 125, 128

 BRAINIAC computer, 88, 117

 Britton, Lionel, 121

 Buffer
   computer, 55
   lexical, 238

 Buildings, automation of, 217

 Burack, Benjamin, 44

 Bureau of Mines, U. S., 189

 Bureau of Ships, U. S., 255

 Burke, Edmund, 32

 Burkhart, William, 45

 Bush, Vannevar, 13, 45, 76

 Business, computer in, 171

 Business management, use of computer, 12, 143

 Butler, Samuel, 32, 33, 121, 252, 268


 CALCULO computer, 75

 _Calculus Ratiocinator_, 109

 Calendars as computers, 24

 California Institute of Technology, 169

 Cancer Society, American, 193

 _Candide_, 30

 Capek, Karel, 43, 121, 215

 Caplin, Mortimer, 150

 Carroll, Lewis, 38, 118

 CDC 1604 computer, 165

 Celanese Corp. of America, 207

 Celestial simulator, 85

 Census, 41

 Census Bureau, U. S., 149

 Chain circuit, 127

 _Characteristica Universalis_, 109

 Charactron tube, 66

 Checkers (game), 8, 143

 Checking, computer, 60

 Checkout computer, 183

 Chemical Corp., 249

 Chess, 8, 9, 16, 35, 99, 142, 156

 Circuit
   chain, 127
   delay-line, 63
   flip-flop, 63, 115
   molecular, 9, 253
   printed, 62
   reverberation, 128

 Clapp, Verner, 248

 Clarke, Arthur C., 265

 CLASS teaching machine system, 226-228

 Clock, 20, 24, 56, 85

 COBOL language, 234

 Code, computer
   binary-coded decimal, 103, 106
   binary-octal, 106
   economy, 106
   excess-3, 105, 114
   “Gray,” 106
   reflected binary, 106
   self-checking, 105

 Color computer, 4

 _Commercial Art_, 175

 Commission on Professional and Hospital Activity, 194

 Communication, use of computers, 179

 Computer
   ADAM, 258
   addition, 106
   airborne, 90, 154, 158, 162
   analog, 21, 45, 72, 74, 80, 125, 203
     direct, 76, 79
     direct-current, 76
     discrete, 80
     indirect, 76, 79
     mechanical differential analyzer, 76
     scaling, 76
   Antikythera, 25
   Apollo, 182
     space vehicle, 169
   applications, digital, 92
   ASCC, 155
   asynchronous, 255
   Athena, 52
   ballistic, 83
   Bendix G-15, 183, 188
   BINAC, 7, 47
   BRAINIAC, 88, 117
   CALCULO, 75
   CLASS, 226-228
   code, binary-coded decimal, 103, 106
   color, 4
   definition, 129
   dictionary, 49, 50
   difference engine, 5, 35
   digital, 18, 45, 73, 84, 125, 203
   division, 107
   do-it-yourself, 75, 88, 117, 147
   electrical-analog, 75
   electronic, 1, 46, 122, 151
   ENIAC, 7, 40, 46, 85, 215
   ERMA, 173
   family tree, 86
   FINDER system, 161
   flow chart, 58, 59
   GE 210, 172
   GE 225, 245
   general-purpose, 54, 81, 191
   gigacycle, 254
   “Hand,” 132, 214, 215
   household, 15, 257
   hybrid, 80, 84, 92
   ILLIAC, 197
   input, 51, 54, 125
   JOHNNIAC, 11, 47, 129, 140, 142
   language, 233
   LARC, 47, 162, 191
   LGP-30, 198
   limitations, 89
   MANIAC, 47, 156, 165
   Memex, 13
   mill, 38, 51, 60
   MIPS, 159
   MOBIDIC, 157
   MUSE, 48
   music, 11, 92, 196, 257
   on-line, 81, 205
   on-stream, 83, 207
   output, 51, 65, 125
   parts, 50, 52, 53
   problem-solving, 140, 143
   Psychological Matrix Rotation, 78, 94
   Q-5, 77
   RAMAC, 150, 151, 198, 199
   Range Keeper Mark I, 42
   RAYDAC, 260
   RCA 501, 151
   “real-time,” 78, 168, 202, 205
   RECOMP, 47
   revolution, 251
   Sabre, 183
   SAGE, 3, 12, 37, 53, 158, 159, 226, 259
   sequential, 126
   “Shoebox,” 242
   “software,” 54
   spaceborne, 167
   special-purpose, 79
   SSEC, 155, 156
   Stone Age, 21
   store, 36, 62
   STRETCH, 47, 48
   subtraction, 106
   testing, 117
   UNIVAC, 47, 149, 151, 171, 221
   VIDIAC, character-generator, 242
   Zuse L23, 199

 Computer Control Co., 260

 Conjunctive operation, 37, 51, 110

 Consciousness, 144, 145, 267

 Continuous analog computer, 80

 Continuous digital computer, 80

 Continuous quantity, 73

 Control, computer, 51, 56

 Control Data Corp., 194

 Conversion
   analog-to-digital, 74
   digital-to-analog, 74

 Converters, 94

 Cook, William W., 29

 Copland, Aaron, 11, 196

 Cornell Medical College, 123

 Cornell University, 133

 Corrigan Communications, 231

 Council on Library Resources, 248

 Counting
   Australian, 20
   birds, 18
   boards, 20
   digital, 84
   machines, 20
   man, 19
   modulo-, 97, 101

 Credit card, 13, 256

 Cryogenics, 70
   components, 63

 Cryotron, 9, 88, 141, 254, 255

 Cybertron, 135, 139

 Cyborg, 265


 Daedalus, 18

 Darwin, Charles, 32, 137, 252

 Data
   link, 14, 185, 256
   logger, 205
   processing, 22, 171, 264
   recording media, 57

 Daystrom, Inc., 211

 Dead Sea Scrolls, 235

 Decimal system, 19

 Decision-making, 91

 Defense, use of computer, 259

 Delay-line circuit, 63

 DeMorgan, Augustus, 38, 110, 115

 Department of Commerce, U. S., 149, 221

 Department of Defense, U. S., 148, 234

 Design, use of computer, 14, 172, 186, 268

 Desk calculator, 51

 Diagnostic use of computer, 194

 Diamond Ordnance Fuze Laboratory, U. S. Army, 69

 Dictionary, computer, 49, 50

 DIDAK teaching machine, 224

 Difference engine, 5, 35

 Digiflex trainer, 225

 Digital computer, 18, 45, 73, 84, 125, 203

 Digital differential analyzer, 94

 Digitronics, 236

 Discrete quantity, 73

 Disjunctive operation, 110

 Division, computer, 107

 Dodgson, Charles L., 38

 Do-it-yourself computer, 75, 88, 117, 147

 Douglas Aircraft Co., 65

 Dow Chemical Corp., 208

 Du Pont Corp., 208

 Dunsany, Lord, 108


 Eccles-Jordan circuit, 47

 Eckert, J. Presper, 47, 85

 EDGE computer system, 185

 Education, use of computers, 219

 _Elan vital_, 127

 Election, use of computers, 150

 Electric Questionnaire, 133

 Electric utilities, use of computers, 93, 208

 Electrical-analog computer, 75

 Electrical logic machine, 44

 Electronic computers, 1, 46, 122, 151

 Elephant, compared with computer, 56

 Encyclopedia Britannica, 6, 226

 ENIAC computer, 7, 40, 46, 85, 215

 _Erewhon_, 32, 121

 ERMA computer, 173

 Ernst, Heinrich, 132, 215

 Euler, 142, 143, 163

 EURATOM, 158


 Family tree, computer, 86

 Farnsworth Car Pool logic problem, 116, 118

 Farrington Electronics, Inc., 240

 Federal Aviation Authority, 149, 161

 Federal Government, 148

 Feedback principle, 36, 204

 Fein, Louis, 260

 Fermat’s theorem, 56

 Ferranti, Ltd., 182

 Ferrite cores, 9, 63, 131, 253

 FIELDATA computer family, 157

 FINDER computer system, 161

 Finn, James D., 224

 Flexibility of digital computer, 89

 Flight simulator, 83

 Flip-flop
   circuit, 47, 63, 115
   fluid, 70

 Floating-point arithmetic, 108

 Flow chart, computer, 58, 59

 Flyball governor, 36, 203

 Fluid computer, 70

 Food Machinery Corp., 249

 Ford Instrument Co., 42

 Forrester, J. W., 199

 _Fortune_, 245

 _Frankenstein_, 42, 212

 Freed, Roy, 152

 Free learning, 7

 Freight trains controlled by computer, 211


 Game-playing, 8, 12, 143

 Gaming theory, 92

 Gardner, Martin, 140

 GE 210 computer, 172

 GE 225 computer, 245

 General Dynamics Corp., 169, 183, 256

 General Electric Co., 10, 45, 67, 76, 77, 79, 171, 172, 240

 General Motors Corp., 218

 General Precision, Inc., 69

 General-purpose computer, 81, 85, 191

 _Gestalt_ principle, 241

 _Giant Brain_, 121

 Gigacycle computer, 254

 Gilfillan Radio, 67

 Glenn, John, 3

 Go (game), 143

 Goal-seeking behavior, 124

 Gödel, Kurt, 135

 “Golem,” 27

 Goodrich Tire & Rubber Co., 188

 Goodyear
   Aircraft Corp., 77
   Tire & Rubber Co., 208

 Goren, Charles, 226

 Government, 258, 263

 Greek numbers, 23

 Grieg, 11

 Grimaldi, 99

 _Gulliver’s Travels_, 30


 Half-adder, 107, 115

 Hamilton, Sir William, 109

 “Hand” computer, 132, 214, 215

 Handwriting reader, 241

 Harcourt-Brace, 226

 _Harvard Business Review_, 171, 172

 Harvard University, 132, 217, 224

 Hawkeye aircraft computer, 162

 Heath, D. C., and Co., 226

 HAYSTAQ, 249

 Heikolator computer, 195

 Hero, 18

 Heuristics, 56, 142

 High-school computer training, 15, 220

 High-temperature susceptibility, 69

 Hilbert, David, 110

 Hiller, Lejaren A., Jr., 197

 Hindu numbers, 23

 HIPO system, 195

 Hippo problem, 155

 Hoffman Electronics Corp., 267

 Holland, James, 224

 Hollerith coding, 42

 Hollerith, Herman, 2, 41, 54, 148

 Holmes, Oliver Wendell, 109

 Homeostat, 124

 Homer, 26, 47

 Hood, H. P. & Sons, 206

 Hoover Commission, 149

 Hourglass, 24

 Household computer, 15, 257

 Hughes Aircraft Co., 203, 215, 222

 Hugo, Victor, 251

 Hybrid computer, 80, 84, 92


 IBM cards, 41

 IBM 704 computer, 8

 IBM 1401 computer, 175

 IBM 1620 computer, 177

 IBM 7074 computer, 175

 Icarus, 18

 Ice cream, computer-made, 206

 ILLIAC computer, 197

 “Illiac Suite,” 196, 197

 _Iliad_, 26, 235

 India, chess legend, 99

 Industrial Advertising Research Institute, 180

 Industrial revolution, 173

 Industry, 181

 “Inflexible Logic,” 32

 Information explosion, 245

 Information retrieval, 14, 243, 246, 247

 Input, computer, 51, 54, 125

 Instamatic computer system, 183

 Insurance, use of computer, 92, 173

 Intellectronics, 258, 262

 Intelligence, 124, 135

 Interagency Data Processing Committee, 148

 Internal Revenue Department, U. S., 150

 International Air Transport Association, 235

 International Association of Machinists, 218

 International Business Machines Corp., 69, 237, 247, 255

 Interlingua, 237

 Inventory, 176, 185

 Inverter, 114, 119

 IRE, 170

 Isaacson, L. M., 197


 Jacquard, Joseph M., 4, 34, 41, 54, 202, 242

 Jet engine simulator, 78

 Jet Propulsion Laboratory, 169

 Jevons, William S., 40

 JOHNNIAC computer, 11, 47, 129, 140, 142

 Johnson’s Wax Co., 178

 Jones & Laughlin Steel Corp., 188, 189, 205

 Journalistor, 64, 252


 Kalin, Theodore, 45, 135

 Kalin-Burkhart machine, 45

 Kane, Sydney, 193

 Kant, Immanuel, 135

 Kelvin, Lord, 75

 Kelvin wheels, 76

 Khayyám, Omar, 108

 KNXT, television station, 179

 Kresge Eye Institute, 195

 Kyoto University, 243


 Lamb, Sydney, 238

 Language, computer, 233

 LARC computer, 47, 162, 191

 Law, 232

 Law Institute, American, 152

 Learning, 123
   forced, 133, 134
   free, 7, 133
   reinforced, 134
   soldered, 7, 133

 Learning, Inc., 226

 Leibnitz, Gottfried, 24, 29, 85, 99, 109, 120

 Lenkurt Electric Co., Inc., 190

 LGP-30 computer, 198

 Library, use of computers, 231

 Limitations of computers, 89

 Lincoln Laboratory, 124

 Lindgren, Astrid, 3

 Literature, computers in, 30

 Litton Industries, 128

 Livanov, M., 133

 Lockheed Aircraft Corp., 185, 248

 Logarithms, 30

 Logic, 38, 90, 108, 229
   Aristotelian, 109
   Farnsworth problem, 116, 118
   mathematical, 110
   symbolic, 38, 109, 110, 115, 248, 255
   unit, 60

 Logical algebra, 40, 108
   piano, 40

 Loom, Jacquard, 34

 Loy, W. D., 23

 Luhn, H. P., 247

 Lull, Ramon, 27, 28, 122

 Lull’s wheel, 28


 _Machine Design_, 180

 Machine shop, use of computers, 209

 Machine Translations, Inc., 239

 MAD, computer language, 220

 Maelzel chess automaton, 35

 Magic squares, 142

 Magnetic cores, 64

 Magnetic disc, 63

 Magnetic drum, 63

 Magnetic films, 88, 255

 Magnetic ink, 3, 240

 Magnetic tape, 55

 Majority rule checking, 60

 Malin, David, 220, 221

 Maloney, Russell, 32

 Management games, 199

 MANIAC computer, 47, 156, 165

 Man-machine relationship, 258

 Mark I computer, 46, 219

 Marquand, Allan, 40, 44

 Matsuzake, Kiyoshi, 21

 Mauchly, John, 47, 85

 Mayans, 24, 97

 McCarthy, John, 170

 McDonnell Aircraft Corp., 186

 McDonough, James, 235

 McDougall, W., 124

 McGraw-Hill Book Co., 226

 Mechanical-relay, 122

 Mediation principle, 102

 Medical diagnosis, 257

 Medical Research Foundation, American, 193

 Medical use of computers, 193

 MEDLARS system, 194

 Memex computer, 13

 “Memistor,” 137

 Memory computer, 51, 63, 254
   BIAX, 10
   MIND, 137
   molecular, 64
   scratch-pad, 63
   unit, 62

 Mercury space capsule, 168, 249

 Merrill Lynch, Pierce, Fenner & Smith, 236

 Michigan State University, 151

 MICR, 240

 “Mill,” computer, 38, 51, 60

 MIND memory unit, 137

 Minneapolis-Honeywell Co., 162, 206, 208, 216

 Minimax theory, 156

 Minuteman missile, 4, 137, 168

 MIPS computer, 159

 MIT, 44, 169, 209, 215, 220

 Mobot, 145, 215, 216, 266

 MOBIDIC computer, 157

 Modeling principle, 83

 Modular approach, 115, 116

 Molecular block memory, 64

 Molecular circuit, 9, 253

 Molecular electronics, 9

 Monsanto Chemical Corp., 208

 “Mooer’s” Law, 245

 Morse code, 99

 Mozart, 11, 197

 Multiplication
   computer, 61, 107
   Russian peasant, 103

 MUSE computer, 48

 Music, 11, 92, 196, 257


 Nanosecond, 61

 NANWEP, 165

 Napier, John, 30

 “Napier’s bones,” 30

 National Library of Medicine, 194

 NASA, 149

 National Bureau of Standards, 94, 239, 249, 258

 National Cash Register Co., The, 240

 National Science Foundation, 158, 249

 Navigation, use of computer, 182

 Navy, U. S., 162

 Negation principle, 113, 114

 Neuristor, 137

 Neurons
   human, 91, 125, 128, 135
   artificial, 136, 138

 Newell, Allen, 141, 251

 Newton, Isaac, 30

 New York University, 194, 220

 Nike missile, 119, 157, 191

 Nim (game), 8, 143

 NORAD, 3, 160, 258

 North American Aviation Corp., 65, 185

 Numbers
   cuneiform, 23
   Arabic, 23
   Babylonian, 23
   binary, 55
   discrete, 73
   Greek, 23
   Hindu, 23
   pure binary, 102, 104
   Roman, 23, 97

 Numerical control, 210

 Numerical weather prediction, 163


 _Odyssey_, 235

 Ohio State University, 222

 On-line computers, 81, 205

 On-stream computers, 83, 207

 _On the Origin of Species_, 32

 Operant reinforcement, 223

 Operations research, 36, 155, 256

 Optical scanning, 240

 OR gate, 112, 113, 117, 119

 _Outline of Psychology_, 124

 Output, computer, 51, 65, 125


 Packaging density, 9, 140

 Paper tape, 54

 Papermaking, 209

 Paradox, 45

 Parallel addition, 107

 Parallel operation, 126

 Parametron, 255

 Parity bit checking, 105

 Parrish, Stephen Maxfield, 235

 Pascal, Blaise, 30, 85

 Patent Office, U. S., 249

 Pauling, Linus, 7, 268

 Pavlov, 133

 Peace Corps, 149, 258

 Peale, Mundy, 125

 PEP system, 186

 Perceptron, 7, 8, 134, 135

 PERT system, 186

 Petroleum industry, 208

 Philadelphia Electric Co., 208

 Philco Corp., 240

 Phillips Petroleum Co., 207

 Phonetic typewriter, 56

 Picatinny Arsenal, 157

 Pierce, John R., 147, 197

 Pitt, William, 39

 Plato, 25, 30

 PLATO computer system, 25, 226

 Player-piano, 54, 68

 “Plot Genii,” 29

 Plotto, 29

 Pneumatic buffering, 69

 Pneumatic capacitor, 69

 Pneumatic computer, 54, 68, 69

 Pneumatic diode, 69

 Pneumatic flip-flop, 69

 Pneumatic inductor, 69

 Poetry computer, 144

 Polaris missile, 4, 162, 168

 Polymorphic data-processing, 264

 Post office, 55, 149, 225

 Potentiometers, 76

 Predictive analysis, 238

 Predictive control, 205

 Prentice-Hall, Inc., 226

 President, 16, 258

 Pressey, Sydney, 222

 Prices, computer, 5, 48, 147

 Primitive equations, 163

 _Principia Mathematica_, 110

 Printed-circuit, 62

 Printers, 65, 66

 Prison, use of computers, 221

 Problem-solving computer, 140, 143

 Process control, 83

 Procter & Gamble, 249

 Program, 52, 226

 Programmer, 55, 56, 103, 104, 128, 233

 Programming, 36, 55

 Psychological Matrix Rotation Computer, 78, 94

 Public Health Service, U. S., 194

 Pueblo Indians, 97

 Punched cards, 2, 34, 41, 42, 43, 54

 Purdue University, 76, 220

 Pure binary, 102, 104


 Q-5 computer, 77


 Radcliffe College, 224

 Radiation effects, 69

 RAMAC computer, 150, 151, 198, 199

 Ramo, Simon, 258, 262

 Rand Corp., 11, 129

 Random-access memory, 63, 131

 Random net, 136

 Range Keeper Mark I computer, 42

 RAYDAC computer, 260

 Raytheon Co., 135, 136

 RCA, 205, 218, 255

 RCA 501 computer, 151

 Reading, by computer, 3, 55, 229

 _Reader’s Digest_, 236

 Real estate, 179

 “Real-time” computers, 78, 168, 202, 205

 RECOMP computer, 47

 Reeves Instrument Co., 77

 Republic Aviation Corp., 125

 Reservations, airline, 3

 Reverberation circuit, 128

 Revolution, computer, 251

 Rheem Califone, 224

 Richardson, L. F., 163

 _Road to Oz, The_, 27

 Robot, 44, 212

 Rockefeller Institute for Medical Research, 194

 Roman numerals, 23, 97

 Rosenblatt, Frank, 133, 135

 Ross, Douglas, 209

 Rossby, C. G., 165

 Royal McBee, Corp., 220

 Royal Society, 251

 _Rubáiyát_, 108

 R.U.R., 44, 121

 Russia, 11, 77, 133, 143, 195, 207, 215, 221, 236, 242

 Russian peasant multiplication, 103

 Russell, Bertrand, 110, 111, 130


 Sabre computer, 183

 SAC, 160, 161

 SAGE computer, 3, 12, 37, 53, 158, 159, 226, 259

 Samuel, Arthur, 251

 Sara Lee Bakeries, 206

 Sausage making by computer, 179

 Scaling, analog computer, 76

 _Scientific American_, 140, 239

 “Sea Wolf” testing by computer, 162

 Second industrial revolution, 171

 Self-reproducing machines, 33, 268

 Selfridge, Oliver, 124

 Sequential computers, 126

 Sex and numbers, 19

 Shannon, Claude, 44, 110, 215

 Shelley, Mary W., 42

 “Shoebox” computer, 242

 Sidewinder missile, 160

 Signal Corps, U. S. A., 77

 Simon, Herbert, 141

 Simulator, 79, 169, 187, 189

 Simulmatics Corp., 181

 Simultaneous linear equations, 77

 Skinner, B. F., 133, 223, 230

 Skybolt missile, 160

 Slide rule, 7, 85

 Smee, Alfred, 121

 Social Security, 149

 “Software,” computer, 54

 Solartron-John Brown, Ltd., 174

 Sonotype, 243

 _Son pan_, 23

 “Sorcerer’s Apprentice,” 27

 _Soroban_, 5, 22

 Southern Methodist University, 179

 Spaceborne computers, 167

 Space flight, 3, 92

 SPADATS system, 160

 Special-purpose computers, 79

 Speech computer, 242

 Sperry Rand Corp., 255

 Sports, use of computers, 198

 SSEC computer, 155, 156

 Standard Oil Co. of California, 207

 Stanhope, Earl of, 39
   demonstrator, 40

 Stapledon, Olaf, 265

 Steel mill, 189, 204

 Steele, J. E., 132

 Stock Exchange, American, 176

 Stock market, 176, 177

 Stone Age computer, 21

 “Store” computer, 36, 62

 Stravinsky, Igor, 197

 STRETCH computer, 47, 48

 Stromberg-Carlson, 191

 “Subroutine” computer program, 59

 Subtraction, computer, 106

 Sumerian cuneiform, 23

 Sundial, 24

 Sun Oil Co., 208

 Supermarket, use of computers, 13, 174

 Surveyor space vehicle, 169

 Swift, Jonathan, 30

 Switch, statistical, 137

 Syllogism, 26, 109

 Symbiosis, 265

 Symbolic logic, 38, 109, 110, 115, 248, 255

 Synnoetics, 260

 SYNTAC, 150

 Synthetic rubber production, 208

 System Development Corp., 156, 220, 226

 Szoeny refinery, 207


 _Tabula rasa_, 126

 Tallies, 20

 Tape memory, 64
   magnetic, 54
   paper, 54

 TASCON, 180

 Taylor, Frederick W., 171

 Teaching machines, 6, 100, 222, 225
   AutoTutor, 213, 225
   CLASS, 226, 227, 228
   DIDAK, 224
   Digiflex, 225
   PLATO, 226
   Pressey, S., 222
   Skinner, B. F., 133, 223, 230
   Videosonic, 222

 Technical Information Service, 249

 Technical Operations, Inc., 150

 Telecredit, 179

 Teleflite, 183

 Testing computers, 117

 Texas Company, The, 208

 Thinking, 123
   molecular theory of, 268

 Thompson Ramo Wooldridge, Inc., 226, 258

 Thomson, James, 75

 Thomson & McKinnon, 177

 Thor missile, 167

 Tick-tack-toe, 8, 143

 Tik-Tok, 27

 Titan missile, 168

 TMI Grolier, 226

 Torres y Quevedo, L., 35

 Trading stamps with computers, 175

 Traffic control, 218

 Trains, 215

 Transcontinental & Western Air Lines, 186

 TransfeRobot, 4, 213, 217

 Transportation, 181

 Transistors, 9, 87, 144

 Translation computer, 91, 92, 237

 Traveling-wave tube, 255

 Truth tables, 110, 112

 Tunnel diode, 255te

 Turing, A. M., 191

 TutorText, 226


 UNESCO, 236

 Unimate, 4, 212, 213

 Union Carbide, 208

 Unitary system, 97

 Unicall, 243

 United Air Lines, 182, 183

 United States Industries, Inc., 213, 218, 225

 UNIVAC computer, 47, 149, 151, 171, 221

 University of California, 76

 University of California at Berkeley, 238

 University of California at Los Angeles, 133, 219

 University of Illinois, 78

 University of London, 8

 University of Michigan, 135, 220

 University of Pennsylvania, 46

 University of Philadelphia, 193

 University of Southern California, 225

 University of Washington, 152

 Upjohn Co., The, 127


 Vacuum tubes, 9, 63, 114, 122

 van Vogt, A. E., 267

 Venn, John, 29, 38

 Videosonic trainer, 222

 VIDIAC character-generator, 242

 Vitruvius, 25

 Vocal computer, 67

 Voltaire, 29

 Voltmeter, 76

 von Braun, Wernher, 168

 von Kempelen, Wolfgang, 35

 von Neumann, John, 130, 137, 156, 251, 253


 Wall Street, 6, 176

 Walter, Grey, 251

 Walnut information retrieval system, 246, 247

 War strategy, 143

 Water clock, 24

 Watt, James, 36, 203

 _Way of All Flesh, The_, 32

 Wearever Aluminum Co., 236

 Weather Bureau, U. S., 166

 Weather map, 164

 Weather prediction, 15, 163

 Wells, H. G., 13, 121

 Werner, Gerhard, 123

 Western Electric Co., 212

 Western Reserve University, 245

 Westinghouse Corp., 76, 211, 218

 Whitehead, A. N., 110, 130

 Wiener, Norbert, 123, 251

 Williams, John, 268

 Wood, Tom, 21

 _World Brain_, 13

 Wright Brothers, 18


 X-15 aircraft, 71, 160


 Young & Rubicam, 181


 Zero, concept of, 24

 Zuse L23 computer, 199

 Zworykin, Vladimir, 194


------------------------------------------------------------------------




 ● Transcriber’s Notes:
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