🚀 go-pugleaf

This article is from Len Popp <tektronix!watmath!watdaisy!lmpopp>
 and was received on Fri Jul 18 20:00:58 1986
 
In article <472@hplabsc.UUCP> Spiros Triantafyllopoulos writes:
>> . . .    Computers *have* been programmed with common-sense rules and
>>information in limited domains (i.e., expert systems).  They sometimes
>>exhibit better "common-sense" reasoning than people, within these domains.
>>What is the theoretical or philosophical reason that these domains could not
>>be extended to the larger but still limited ones that humans use?
>>
>
>Nope. Expert systems have been known for behaving perfectly when faced
>with situations for which the appropriate rule/action pairs exist. However,
>expert systems can fail pretty miserably when faced with situations
>beyond the scope of their knowledge.

"Nope" to what???   I never said that expert systems could reason outside
their domains, just that people can't either!!!!  Compare:

	People have been known for behaving (almost) perectly when faced
	with situations for which they have appropriate experience or
	knowledge.   However, common sense can fail pretty miserably when
	faced with situations outside of everyday experience.

Is not that just as true as your statement about expert systems?  Are you
really trying to say that because humans have MORE "appropriate rule/action
pairs" (i.e., knowledge or experience) that our common sense covers ALL
situations in the universe?  Don't be silly!  I won't bore you with
examples, because I'm sure you can come up with your own, but surely it is
obvious that there are a great many situations not covered by human common
sense.  The major difference between the limited scope of expert systems and
the limited scope of common sense is one of degree.  I still claim that the
reason that computer "common sense" only works within small domains is that
we have never programmed a computer with all the rules covering a large
domain of problems.  And the reason that this hasn't been done is not
because we don't know how to build expert systems, but because we don't
really understand the reasoning behind our "common sense".  In other words,
the knowledge built into current expert systems is limited by *our*
knowledge.  We can't explain what we don't understand.

>
>Most peoples' idea of expert systems comes from quite inflated claims
>by software developers/research-paper-writers/and-the-like. An article
>in AI magazine about a year ago discussed this phenomenon quite extensively.
>Claims of 90% success etc. were usual, but nowhere where the limitations
>and/or failures of the presented system (typical let-the-user-find-out
>conditions). There have been cases of expert systems working with VERY
>specialized problems (where common sence wouldn't do much good anyway)
>therefore paving the way for generalization of claims about expert systems
>in general. But we're a long way from getting there.

My claim that expert systems have been made to reason within small domains
was not based on advertising or media claims, but on documented performance
of expert systems.  I agree that many of the claims in ads and popular
articles are utterly ridiculous.  (It seems that any program with a slightly
clever algorithm or data structure is using "AI", these days.)

However, how is reasoning on "VERY specialized problems" different from
common sense?  Our "common sense" is limited to the domain of phenomena
encountered in everyday human life, which is also very specialised in the
grand scheme of things.  And since when does common sense *not* do much good
to, for example, doctors diagnosing diseases, or chemists trying to divine
the structure of organic molecules from indirect data?  Again, I say that
the difference between computer "common sense" and human "common sense" is
that we haven't figured out enough of our common sense to tell it to a
computer.  That's not a reflection on the computer.


							   Len Popp
{allegra,decvax,ihnp4,tektronix,ubc-vision}!watmath!watdaisy!lmpopp