From newshub.ccs.yorku.ca!ists!helios.physics.utoronto.ca!news-server.csri.toronto.edu!rpi!think.com!ames!agate!stanford.edu!leland.Stanford.EDU!leland.Stanford.EDU!shibe Mon Mar  9 18:34:45 EST 1992
Article 4216 of comp.ai.philosophy:
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>From: shibe@leland.Stanford.EDU (Eric Schaible)
Subject: Re: Reference (was re: Multiple Personality Disorder and Strong AI)
Message-ID: <1992Mar3.075854.6444@leland.Stanford.EDU>
Keywords: Housebreaking your dogma
Sender: news@leland.Stanford.EDU (Mr News)
Organization: DSG, Stanford University, CA 94305, USA
References:  <1992Mar2.223923.1711@oracorp.com>
Date: Tue, 3 Mar 92 07:58:54 GMT
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In article <1992Mar2.223923.1711@oracorp.com>, daryl@oracorp.com writes:

>but I don't see why any of the supposed
>limitations on a computer's ability with semantics do not also apply
>to human beings.

[section deleted]

>Now, the question arises: is the information that the baby received
>sufficient to determine the meaning of the word "hamburger"? Is there
>only one meaning of the word "hamburger" that is consistent with that
>information?
>
>If the answer to the latter question is "yes", then it would appear
>that signal processing is sufficient to determine the semantics of
>words, and so there is no a priori reason to believe that a computer
>is incapable of it. If the answer is "no" (which I think would be the
>position of Putnam et. al.), then we still have no reason to think
>that a human can do something that a computer cannot, since we have no
>reason to think *humans* can determine the semantics of words.
>
>Daryl McCullough
>ORA Corp.
>Ithaca, NY

I think that your criterion of 'determining' semantics is unreasonably
strong, and is probably the result of carrying the "computer metaphor" of
the mind a little too far.  Experience with current computers tells us
that yes, of course, everything is determinate; processing is entirely
formal and discrete.  Moreover, the computer metaphor leads us to believe 
that if humans utilize semantics, they should be able to access the meaning 
of a word, and that this is how they comprehend language--they access the 
meanings which they have stored and compile them according to stored rules 
about grammar, pragmatics, etc.

I will argue:  humans cannot determine semantics in your sense; however,
they do not need to.  

I think the following view is more reasonable:  Humans do not access
meanings of words; rather, they interpretively construct meanings in an
ad hoc, context-dependent way.  When you ask someone to give you a
definition of a word apart from a context of use, they can give you a
generalization of the ways in which they use the word; but this is merely
a generalization--an abstraction from the more fundamental process of
context-based interpretation.

How does this relate to your argument?  As follows:  it leads me to
believe that humans are doing something that current computers are not.
I agree that humans cannot determine (in your sense) the semantics of
the word 'hamburger'.  However, I do not conclude from this that humans
do not understand the word 'hamburger', especially when it is used in a
context.  So "NO"--there is not a single meaning of the word 'hamburger';
rather, there is a body of experience with the uses of the word 'hamburger'
that is drawn upon to interpret the meaning of the use in each particular
case.   But "YES"--humans still derive information from the process of
interpretation, and can understand what they are processing, despite the
fact that they cannot give you a well-defined model-theoretic statement and/or
primitive-based compositional tree structure which encompasses and 
explains all possible uses and truth-conditions for the term 'hamburger'.

In contrast, for current computers it is clear that if the
so-called-semantics are not discrete and formal, then processing is
impossible.  The absurdly complete and well-defined semantic structure 
mentioned above is exactly what is needed for the computer to do the job.
Moreover, it is needed BECAUSE the system possesses no way of understanding the
term--since the computer has no understanding, one needs to make every
possible application explicit.

To sum up:  for the human, there does not need to be one determinate, well-
defined meaning; for current computers, there does.  Your application of the
computer metaphor of the brain leads you (I think incorrectly) to assume 
that the computer's need for formalism must apply to humans as well.  As a
result, you conclude (again, I think incorrectly) that if a human cannot
apply or generate a determinate semantic representation, the human cannot
gain information from processing.

Eric Schaible

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