saal@sfsup.UUCP (S.Saal) (03/31/88)
I think the pessimism about AI is a bit more subtle. Whenever something is still only vaguely understood, it is considered a part of AI. Once we start understanding the `what,' `how,' and (sometimes) `why' we no longer consider it a part of AI. For example, all robotics used to be part of AI. Now robotics is a field unto itself and only the more difficult aspects (certain manipoulations, object recognition, etc) are within AI anymore. Similarly so for expert systems. It used to be that ES were entirely within the purview of AI. That was when the AI folks had no real idea how to do ESs and were trying all sorts of methods. Now they understand them and two things have happened: expert systems are an independant branch of computer science and people have found that they no longer need to rely on the (advanced) AI type languages (lisp, etc) to get the job done. Ironically, this makes AI a field that must make itself obsolete. As more areas become understood, they will break off and become their own field. If not for finding new areas, AI would run out of things for it to address. Does this mean it isn't worth while to study AI? Certainly not. If for no other reason than AI is the think tank, problem _finder_ of computer science. So what if no problem in AI itself is ever solved? Many problems that used to be in AI have been, or are well on their way to being, solved. Yes, the costs are high, and it may not look as though much is actually coming out of AI research except for more questions, but asking the questions and lookling for the answers in the way that AI does, is a valid and useful approach. -- Sam Saal ..!attunix!saal Vayiphtach HaShem et Peah HaAtone
boris@hawaii.mit.edu (Boris N Goldowsky) (04/03/88)
In article <2979@sfsup.UUCP> saal@sfsup.UUCP (S.Saal) writes:
Ironically, this makes AI a field that must make itself obsolete.
As more areas become understood, they will break off and become
their own field. If not for finding new areas, AI would run out
of things for it to address.
Isn't that true of all sciences, though? If something is understood,
then you don't need to study it anymore.
I realize this is oversimplifying your point, so let me be more
precise. If you are doing some research and come up with results that
are useful, people will start using those results for their own
purposes. If the results are central to your field, you will also
keep expanding on them and so forth. But if they are not really of
central interest, the only people who will keep them alive are these
others... and if, as in the case of robotics, they are really useful
results they will be very visibly and profitably kept alive. But I
think this can really happen in any field, and in no way makes AI
"obsolete."
Isn't finding new areas what science is all about?
Bng
--
Boris Goldowsky boris@athena.mit.edu or @adam.pika.mit.edu
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