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From: thornley@cs.umn.edu (David H. Thornley)
Newsgroups: talk.philosophy.misc,comp.ai
Subject: Re: Why the Chinese Room doesn't convince
Message-ID: <1990Apr13.182640.5694@cs.umn.edu>
Date: 13 Apr 90 18:26:40 GMT
References: <1990Apr11.173241.6428@maths.tcd.ie>
Organization: University of Minnesota, Minneapolis - CSCI Dept.
Lines: 116

In article <1990Apr11.173241.6428@maths.tcd.ie> ftoomey@maths.tcd.ie (Fergal Toomey) writes:
>In article <1990Apr10.202829.2080@cs.umn.edu> thornley@cs.umn.edu
>(David H. Thornley) writes:
>
>>I seriously question the validity of this.  The number of possible
>>positions is sufficiently high that it may as well be infinite, since
>>it is not possible to enumerate them (at, say, a thousand per second)
>>within the expected lifespan of the universe, nor would a human-readable
>>version come anywhere near fitting on this planet.
>>
>>Therefore, the list is impossible.  The novice must have something else
>>from Kasparov, perhaps a computer program or a chess book of a quality
>>never yet approached.
>
>Well, chess came up as a convenient example. Replace with Tic-Tac-Toe
>and everything becomes reasonable. I expect that we'll keep the chess
>example, however, because *in principle* it is the same as Tic-Tac-Toe
>(ie. the ideas involved in understanding chess are the same as those
>involved in understanding Tic-Tac-Toe... probably... oh dear.. :-) ).
>
>> David Thornley
>
>Fergal Toomey.

Here is my position:

I believe that understanding is inferred from behavior.  For my first exhibit,
consider an elementary algebra student.  I wish to determine whether she
understands polynomial multiplication.  How can I determine this?

1.  I can ask her to explain how to do it.  Any answer of the form of 
"multiply all the parts of one polynomial by all the parts of the other one,
then add everything together" is acceptable.

2.  I can give her several problems, some of them involving more than one
polynomial.

3.  I can ask her to prove that what she is doing is valid, applying the laws
of distributivity and commutativity and associativity.

4.  I can assume that I am human, she is human, and I understand polynomial
multiplication, hence she should be able to.

5.  I can try to use brain-imaging techniques and massive psychological
tests to determine the changes in her mind that have resulted from her
learning algebra.

Techniques 1, 2, and 3 are simply behavior-based.  Technique 5 is impractical
because I haven't the faintest idea of what to look for.  I don't know how it
is that I understand algebra (although I do), how should I know how anyone
else does it?

Technique 4 is, of course, only a plausibility argument, but I think it is
a major force in thinking about computer understanding.  Understanding is a
very slippery concept, as we have seen in this thread, and there seems to
be extreme reluctance to apply it to nonhumans on a serious basis (as 
opposed to such things as verbally encouraging ones car or bowling ball to 
behave in a desired manner).  I believe that we are preprogrammed from birth
to recognize that other humans are like us, as otherwise I don't understand
how so many of us would believe that at such an early age.

Therefore, we need to decide how much more difficult we are to make it to
consider that a machine understands something than a human.  How much of
the human prejudice is rational observations that we know that humans can
understand things and how much is irrational conviction that humans are the
only things that can understand?

Also, if we are to discuss whether machines understand, we have to come up
with some criterion, or we are merely wasting bandwidth.  If someone wishes
to argue that machines cannot really think or understand, since these are
properties of souls and machines do not have souls, I can't argue with that.
If someone wishes to argue that the Universe is one large mind and that 
everything understands, my only argument is that this isn't what I mean by
understanding.  It seems to me that the only possible criteria are static
and dynamic analysis.  Static analysis, such as the analysis of algorithms,
seems to me to fail on the grounds that we don't know what we are looking for.
If we knew how people understood things, it would be possible to determine
what constraints we could put on understanding.  Since we don't, we can't.

This leaves dynamic analysis, or behavior.  I think that most people would
accept a machine as truly intelligent and understanding if it acted as such
and the people had enough contact with it to realize that.  I think that
this would be an almost automatic and completely correct conclusion.

We must also consider that behavior is finite.  As a matter of rational
expectation, I am probably not going to live another sixty years.  In this
time, I cannot talk faster than about 150-200 words per minute, I type slower
than that, and my actions take time.  Therefore, I can put strict limits on
the amount of words and deeds I can produce for the rest of my life.  In
this case, it seems that we have to put a time and output limit on any
Turing test of understanding.  This is why I object to thought experiments
in behavior that involve tasks that are not possible to complete while this
Universe is still capable of harboring intelligent life.

I would like, then, to return to static analysis of understanding.  How do
we generally use the concept?  We do not generally consider table look-up
to be understanding, and so we would say that a Tic-Tac-Toe novice looking
move up off a list of game positions is not showing understanding of the
game.  Since this is not possible with chess, we can assume that a good
chess-playing system may be showing some understanding of the game.

This is why I am insisting on not allowing a list of all possible chess
positions in the argument.  It is just as possible to construct a list of
all possible written conversations as it is to construct a list of all
possible chess positions:  theoretically doable (if we limit the length of
the conversations, perhaps to one trillion words each) and totally impossible
within the limits of the Universe we live in.  Any task that we would
consider setting to an unknown system to determine understanding could
be satisfied with list look-up, since we cannot set infinite tasks.  However,
most tasks of even moderate complexity could not be satisfied with lists
produced under any reasonable conditions.

Therefore, I claim that it is reasonable to base understanding on complex
behaviors, and that this is the only practical way we have right now.

David Thornley