From: lyman@casbah.acns.nwu.edu (Kenneth Casey)
Subject: Re: Problems with AI: goals, structure, mechanics
Organization: Northwestern University, Evanston Illinois.
Date: Mon, 12 Oct 1992 23:35:16 GMT

In article <KPC.92Oct11202103@zog.arc.nasa.gov> kpc@ptolemy.arc.nasa.gov writes:
>In article <1992Oct5.011143.8020@hellgate.utah.edu> tolman%asylum.cs.utah.edu@cs.utah.edu (Kenneth Tolman) writes:
>
>   What, in your opinion, are the fundamental problems with artificial 
>   intelligence research today?
>
>it seems to me as follows.  i would be glad to be corrected or
>persuaded otherwise!  i solicit comments on this!
>
>(1)
>
>there are diverging goals.  half of us try to make computers do useful
>and interesting things; the other half try to learn something about
>the brain and the mind using computers.
>
>the first half could perhaps work more closely with operations
>research types, while the second half could perhaps work more closely
>with cognitive psychologist types.  the first half can be a blessing
>to our economy; the second half can be a blessing to our knowledge.
>
>at one time, the two were closer, i suppose, with heuristic search
>being one unifying paradigm.  now, there is a pluralism of techniques
>(sometimes it seems like the technique-of-the-month club!), and they
>don't have much in common, much less find expression in search terms.
>
>it seems hard these days for somebody who does, say, planning, to keep
>up with vision, or even to share new fundamental knowledge.  sometimes
>we have different subfields tackling problems with very similar
>structures, using different terms to describe their solutions.  is
>this natural?  will the knowledge ever transfer?  will there ever be
>anything to unify the different subfields again?  i would be
>interested in comments.
>
>(2)
>
>another problem is that there are lots of people doing very good work,
>but the field seems dominated somehow by a relatively small number of
>people who, while they are usually doing good work too, have lots of
>power in the field.  it sometimes seems like it's harder for young
>researchers to make names for themselves than it was earlier in the
>field's history.
>
>and yet, somehow, those who make names for themselves sometimes seem
>not to do things of huge import to the work of others in the field
>(some do, don't get me wrong, but inventing a dubious new technique
>and not showing its relation to other techniques makes it difficult to
>judge its usefulness, imho).  maybe it's just demographics and the
>natural course of fields, or maybe it's the mechanics of such work
>combined with other factors.  i would be interested in comments.
>
>(3)
>
>another problem is that programs get huge and ugly, and take a long
>time to write, debug, and make presentable, much less share code with
>other programs.
>
>did i describe ai correctly?  any comments from other ai types?
>
>and for you cognitive psychologist types, what are the problems of
>cognitive psychology?  are they similar?  (i've heard the criticisms
>that (1) people in psychology are just as trendy, going from "effect"
>to "effect" and (2) people in psychology try to make their field look
>more rigorous than it is by dressing up conjectures in math.)
>
>(i have a hidden agenda in asking: i am thinking of switching from ai
>to cogpsych and i'd like to know whether i am doing the right thing!)


	As a first year grad student in cognitive, I'm hardly qualified
to hold forth on the great problems of the field. But from a distance
that's growing shorter by the day, I can see a couple issues. First, the
rigorousness of the experiment is sometimes constrained by ill-defined
phenomena. For example, a researcher exploring motivation-cognition
interactions has her or his hands full just defining motivation. This same
problem often leads to some of the "effect to effect" tendency you noted. The
goal of this  micro-psych stuff is to allow us to grope upwards toward a
better understanding of the larger phenomena. Anyway, it's an enormous field
with a lot of areas to choose from, some investigating more well defined
constructs than others. Personally, I think part of the challenge is to
avoid the pitfall of being too reductionist in our eagerness to be scientific,
while at the same time not allowing ourselves to drift off into mysticism...
Anyway, that's my 2cents.
Newsgroups: sci.cognitive