abc%brl-bmd@sri-unix.UUCP (12/02/83)
From: A B Cooper III <abc@brl-bmd>
Being nothing more than an amateur observer on the AI scene,
I hesitate to plunge in like a fool.
Nevertheless, the roundtable on what constitutes intelligence
seems ed to cover many interesting hypotheses:
survivability
speed of solving problems
etc
but one. Being married to a professional educator, I've found
that the common working definition of intelligence is
the ability TO LEARN.
The more easily one learns new material, the
more intelligent one is said to be.
The more quickly one learns new material,
the more intelligent one is said to be.
One who can learn easily and quickly across a
broad spectrum of subjects is said to
be more intelligent than one whose
abilities are concentrated in one or
two areas.
One who learns only at an average rate, except
for one subject area in which he or she
excells far above the norms is thought
to be TALENTED rather than INTELLIGENT.
It seems to be believed that the most intelligent
folks learn easily and rapidly without
regard to the level of material. They
assimilate the difficult with the easy.
Since this discussion was motivated, at least in part, by the
desire to understand what an "intelligent" computer program should
do, I feel that we should re-visit some of our terminology.
In the earlier days of Computer Science, I seem to recall some
excitement about machines (computers) that could LEARN. Was this
the precursor of AI? I don't know.
If we build an EXPERT SYSTEM, have we built an intelligent machine
(can it assimilate new knowledge easily and quickly), or have we
produced a "dumb" expert? Indeed, aren't many of our AI or
knowledge-based or expert systems really something like "dumb"
experts?
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You might find the following interesting:
Siegler, Robert S, "How Knowledge Influences Learning,"
AMERICAN SCIENTIST, v71, Nov-Dec 1983.
In this reference, Siegler addresses the questions of how
children learn and what they know. He points out that
the main criticism of intelligence tests (that they measure
'knowledge' and not 'aptitute') may miss the mark--that
knowledge and learning may be linked, in humans anyway, in
ways that traditional views have not considered.
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In any case, should we not be addressing as a primary research
objective, how to make our 'expert systems' into better learners?
Brint Cooper
abc@brl.arpa