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From: WALKER@SUMEX-AIM.ARPA
Newsgroups: net.ai
Subject: response to response to challenge
Message-ID: <14111@sri-arpa.UUCP>
Date: Wed, 23-Nov-83 21:02:11 EST
Article-I.D.: sri-arpa.14111
Posted: Wed Nov 23 21:02:11 1983
Date-Received: Thu, 1-Dec-83 21:26:01 EST
Lines: 51

From:  Michael Walker <WALKER@SUMEX-AIM.ARPA>

Tom,

        I thought you made some good points in your response to Ralph
Johnson in the AIList, but one of your claims is unsupported, important,
and quite possibly wrong. The claim I refer to is

        "Expert systems can be built, debugged, and maintained more cheaply
        than other complicated systems. And hence, they can be targeted at
        applications for which previous technology was barely adequate."

        I would be delighted if this could be shown to be true, because I
would very much like to show friends/clients in industry how to use AI to
solve their problems more cheaply.

        However, there are no formal studies that compare a system built
using AI methods to one built using other methods, and no studies that have
attempted to control for other causes of differences in ease of building,
debugging, maintaining, etc. such as differences in programmer experience,
programming language, use or otherwise of structured programming techniques,
etc..

        Given the lack of controlled, reproducible tests of the effectiveness
of AI methods for program development, we have fallen back on qualitative,
intuitive arguments. The same sort of arguments have been and are made for
structured programming, application generators, fourth-generation languages,
high-level languages, and ADA. While there is some truth in the various
claims about improved programmer productivity they have too often been
overblown as The Solution To All Our Problems. This is the case with
claiming AI is cheaper than any other methods.

        A much more reasonable statement is that AI methods may turn out
to be cheaper / faster / otherwise better than  other methods if anyone ever
actually builds an effective and economically viable expert system.

        My own guess is that it is easier to develop AI systems because we
have been working in a LISP programming environment that has provided tools
like interpreted code, interactive debugging/tracing/editing, masterscope
analysis, etc.. These points were made quite nicely in Beau Shiel's recent
article in Datamation (Power Tools for Programming, I think was the title).
None of these are intrinsic to AI.

        Many military and industry managers who are supporting AI work are
going to be very disillusioned in a few years when AI doesn't deliver what
has been promised. Unsupported claims  about the efficacy of AI aren't going
to help. It could hurt our credibility, and thereby our funding and ability
to continue the basic research.

Mike Walker
WALKER@SUMEX-AIM.ARPA