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From: tsmith@gryphon.CTS.COM (Tim Smith)
Newsgroups: comp.ai
Subject: The Success of AI
Message-ID: <1922@gryphon.CTS.COM>
Date: Fri, 16-Oct-87 02:07:47 EDT
Article-I.D.: gryphon.1922
Posted: Fri Oct 16 02:07:47 1987
Date-Received: Sat, 17-Oct-87 18:47:03 EDT
Reply-To: tsmith@gryphon.CTS.COM (Tim Smith)
Organization: Trailing Edge Technology, Redondo Beach, CA
Lines: 77

There is one humbling sense in which the work in AI in the
past 20 or so years will help considerably in the ultimate
understanding of human intelligence. If you look at concepts
of the brain in the recent past, you see that whatever was
the most current technological marvel served as a metaphor
for the brain. In the early 20th century the brain was a
telephone exchange. After WWII, the systems organization
metaphor was often used (the brain was a large corporation,
with a CEO, VPs, directors, etc.).

It wasn't until computers came along that there was a
metaphor for the brain powerful enough to be taken seriously.
Once people started to try to imitate their brains on
computers, some limitations became apparent. Interestingly
enough, the limitations are not so much in the technological
metaphor as in the present concept of the brain, or of the mind
in general.

There is no reason, in principle, that a very powerful
digital computer cannot imitate a mind, *as long as a mind
is some kind of abstract logic machine*.  What AI has
discovered (though it is very unwilling to admit it) is that
this Cartesian (or even Platonic) concept of the mind is
hopelessly inadequate as a basis for understanding human
intelligence!

To conceive of the human mind as a disembodied logic machine
seemed like a great breakthrough to scientists and
philosophers. If it was this, it could be studied and
understood. If it wasn't this, then any scientific study of
the mind (hence, of intelligence) appeared to be fruitless.

The success rate in AI research (as well as most of cognitive
science) in the past 20 years is not very encouraging.
Predictions, based on very optimistic views of the problem
domain, have not been met. A few successful spin-offs have
occurred (expert systems, better programming tools and
environments), but in general the history is one of failure.
Computers do not process natural language very well, they cannot
translate between languages with acceptable accuracy, they
cannot prove significant, original mathematics theorems.

What AI researchers and other cognitive scientists now have to
face is fairly clear evidence that simulations of human
intelligence, where human intelligence is modelled as a
disembodied logic machine, are doomed to fail. Better hardware
is not the solution.  Connection machines or simple silicon
neural nets are not the answer. A better concept of "mind" is
what is needed now. This is not to say that AI research should
halt, or that computers are not useful in studying human
intelligence. (They are indispensable.) What I think it does
mean is that one or more really original theoretical paradigms
will have to be developed to begin to address the problems.

One possible source of a new way of thinking about the problems
of modelling human intelligence might be found in a revolution
that is beginning in the cognitive sciences. This revolution is
of course not accepted by most cognitive scientists; many are
not even aware of it. It is difficult to characterize the
revolution, but it essentially rejects the Cartesian dualism of
mind and body, and recognizes that an adequate description of
human intelligence must take into account aspects of human
physiology, experience, and belief that cannot *now* be modelled
by simple logic (e.g., programs).  For one example of this new
way of thinking, see the recent book by the linguist George
Lakoff, entitled "Women, Fire, and Dangerous Things."  (Neither
the book nor the title are frivolous.)

I believe the great success of AI has been in showing that
the old dualistic separation of mind and body is totally
inadequate to serve as a basis for an understanding of human
intelligence.
-- 
Tim Smith
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