From: kpc@pluto.arc.nasa.gov (k p c)
Subject: Problems with AI: goals, structure, mechanics
Reply-To: kpc@ptolemy.arc.nasa.gov
Organization: NASA Ames Research Center AI Research Branch; Sterling.
Date: Mon, 12 Oct 1992 04:21:03 GMT

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!)