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From: Spencer.Star@H.GP.CS.CMU.EDU.UUCP
Newsgroups: comp.ai.digest
Subject: Re: AIList V5 #201 - Philosophy of Science, AI Paradigms
Message-ID: <556829438.star@h.gp.cs.cmu.edu>
Date: Mon, 24-Aug-87 14:50:00 EDT
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Posted: Mon Aug 24 14:50:00 1987
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In V5 #201 Andrew Jenning suggests that AI is empirical research when a
programmer writes a program because we have some definite criteria:
either the program works or it does not.  Unfortunately, this view is
rather widespread.  Also, it is wrong.  Empirical research seeks to
make general statements of a quantitative nature.  For example, the
measurement of the speed of light gives us a value that is applicable
in general, not just Tues July 15th in Joe's lab.  A psychologist who
measures the reaction time of a person before and after drinking
alcohol is making an empirical statement that should hold in other labs
under other similar experimental conditions.  The central ideas of
empirical research is that results be publically repeatably, and lead
to some generalizations.   If it happens that the results confirm or
disconfirm some theoretical predictions, so much the better.  A
programmer who gets a program to work says nothing more scientific than
a plumber who has cleared a drain or a dentist who has filled a tooth.
In most cases there was no theory being tested, there is no
generalization that can be made, the work is handcrafted and cannot be
repeated in another lab based on the public description of what was
done, and we cannot even be sure that the program works on anything
more than the specific examples used in the demonstration.  At best
such a program is an example of craftsmanship and programming skills.
It has nothing to do with scientific research.  

Spencer Star
(star@h.cs.cmu.edu)