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From: tanner@osu-eddie.UUCP
Newsgroups: comp.ai
Subject: Re: dear abby....
Message-ID: <3269@osu-eddie.UUCP>
Date: Mon, 2-Mar-87 10:58:29 EST
Article-I.D.: osu-eddi.3269
Posted: Mon Mar  2 10:58:29 1987
Date-Received: Tue, 3-Mar-87 20:20:28 EST
References: <178@arcsun.UUCP>
Reply-To: tanner@osu-eddie.UUCP (Mike Tanner)
Organization: The Ohio State University, CIS Dept.
Lines: 27
Keywords: justification in expert systems


Leaving aside the utility of explanations in developing a system and
in convincing users it is behaving properly there is this:

     Experts are capable of explaining their reasoning, justifying
     conclusions, etc.  Hypothesis:  they are able to do this partly
     because of the way their knowledge is organized and used in
     problem-solving.  

Therefore, if your expert system is incapable of explaining itself you
probably haven't got the knowledge organization and problem solving
strategy right.  (Granted, it's only a hypothesis.  It seems right to
me.  I'm in the process of working on a PhD dissertation on how
knowledge organization and problem-solving strategy can help produce
good explanations.  Doesn't exactly support the hypothesis, but it
should clarify it a bit.)

This assumes you're interested in how knowledge-based problem-solving
works.  If all you want is an expert system, ie, a system which gets
right answers, then you're back to utility arguments for explanation.
(Though, I don't think you'll be successful at getting good
performance without this understanding.)

-- mike

ARPA:  tanner@ohio-state.arpa
UUCP:  ...cbosgd!osu-eddie!tanner