The Best of Creative Computing Volume 2 (published 1977)

Page 43 << PREVIOUS >> NEXT Jump to page:
Go to contents Go to thumbnails
This book is also available for the Kindle

The Thinking Computer (from the book The Thinking Computer: Mind Inside Matter, 1976; Misleading Myths, The Arithmetic Myth, The Stupid Computer Myth, Problem Solving Methods)
by Dr. Bertram Raphael

graphic of page

Misleading Myths

Many people believe that computers are inherently
stupid, and think that even a suggestion that computers
might be made smarter is ridiculous. This belief is so widespread that most
people never even consider the many
ways in which smarter computers might help them. Misconceptions about a
computer's limitations seem to be
based upon two widely accepted but basically untrue
premises. Let us examine these myths. By pointing out
some of their fallacies, perhaps I can open your mind to the
fascinating prospects for smarter computers.

THE ARITHMETIC MYTH. A computer is nothing but a big
fast arithmetic machine.

Computers are arithmetic machines, certainly; almost
every computer has wired into it ability to add and
subtract. But are they "nothing but" arithmetic machines?

Certainly not. Take the reference manual for any computer,
and scan through its "instruction set": the collection of
basic operations it has been designed and wired to perform.

You will see a few, perhaps as many as ten or twenty, operations that bear some
close resemblance to arithmetic-e.g.,
so on-but you will also see many, perhaps one or two
hundred, operations that have relatively little to do with
arithmetic-eg., STORE, LOAD, TEST, SHIFT, READ,
TRANSFER. and so on. Much of the time that any computer
works on any problem, the computer is positioning, comparing, moving, choosing,
copying ..., but it is not doing
arithmetic, Rather than calling a computer "nothing but a
big fast arithmetic machine," it is much more accurate to
say that a computer is a big, fast, general-purpose symbolmanipulating machine.

obedient intellectual slave that can do only what it is told to

This second myth is even more persistent than the first
one, and even more damaging in the way it tends to constrain our thinking.
Suppose I gave you the pieces of a jigsaw puzzle and told you, "by the way,
these pieces cannot
be fitted together." Would you try very hard to fit the pieces
together? Why should anyone try to build a smart computer,
if he is told over and over again that computers are
inherently stupid?

The stupid-computer myth has been repeated and generally accepted for more than
a hundred years. In 1842,
after Professor Babbage of Cambridge designed his
Analytical Engine, a large-scaled mechanical digital
computer (which unfortunately was never completed), his
friend Lady Lovelace wrote, "The Analytical Engine has no
pretensions to originate anything. It can do whatever we
know how to order it to perform," There is no question that
Lady Lovelace's argument, and all the subsequent versions of the stupid-computer
myth, are true, in a certain
literal sense: a computer must be given its program of instructions, and it will
always do exactly what those instruc
This article consists largely of material from the book, THE
THINKING COMPUTER: Mind Inside Mattel, by Dr. Bertram
Raphael which will be published early in 1976 hy W.H. Freeman
and Company.

As novel sources of information,
amusement, or artistic experiences,
the potential for us to benefit from
thinking computers is limited only by
our imaginations.

tions tell it to do (unless, of course, one of its circuits fails).

And yet this basic truth is not a real restriction on the intelligence of
computers at all.

The claim that a computer "can only do what it is told to
do" does not mean that computers must be stupid; rather, it
clarifies the challenge of how to make computers smarter;
we must figure out how to tell (i.e., program) a computer to
be smarter. Can we tell a computer how to learn? To create?

To invent? Why not? I'd bet even Lady Lovelace would have
agreed that the task of figuring out "how to order" a
computer "to originate" something would be a fascinating
and meaningful research challenge.

Progress in "artificial intelligence," the study of how to
make computers smarter, is now enabling computers to
apply a wide range of problem-solving methods; to communicate in ordinary
English; to perceive the physical
world; and to combine such abilities into flexible systems
that perform useful tasks. The following paragraphs review
some of this progress.

Problem-solving Methods

How do most people solve common, everyday problems?

Suppose Mr. Pollack is driving to a ski resort in his little
foreign car. On the way he encounters a snow Storm, and
finds he must mount his brand new tire chains on the
wheels of his car. This problem-how to mount the chains
on the wheels-can be divided into many little subproblems. Do the chains go on
the from or the rear wheels?

Should they be wrapped around a wheel by jacking the
wheel off the ground, by driving the car onto the chains, or
by figuring out how to use the funny little "mounting tools"

that come with the chains? Which side of the chains should
be up? How does the peculiar linking mechanism work? And
so on. Mr. Pollack must solve these problems as quickly as
possible, so that he can accomplish the task without freezing his fingers and
soaking his clothes, and so that he can
still get to the ski area without missing too much of the day's
activities. Well, exactly how is this kind of problem usually
attacked? By encoding the known facts into mathematical
axioms, and using theorem-proving methods? Not likely!

Instead Mr. Pollack (and millions of others) use informal
problem-solving methods.

Informal problem-solving methods are especially intriguing because of their
extreme generality. Problem-solving
methods that most scientists develop work only in highly
specialized, highly technical areas: e.g., a method for solving second-order
linear differential equations with constant coefficients, or a method for
estimating the distances
of stars less than twenty light years away. Informal
problem-solving methods, in contrast, seem to be
applicable to a wide variety of problems, most of which may
be brand new to the person using the methods: even though
Mr. Pollack may never have been called upon to mount tire
chains before, he need not be at a total loss as to how to
proceed. ls there some standard way of viewing any task,
that enables people to apply their reasoning abilities with
flexibility to any problem that arises? Psychologists have
developed various approaches to explaining such complex
cognitive behavior. One approach that has been embodied


Page 43 << PREVIOUS >> NEXT Jump to page:
Go to contents Go to thumbnails
This book is also available for the Kindle