Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!usc!isi.edu!vaxa.isi.edu!smoliar
From: smoliar@vaxa.isi.edu (Stephen Smoliar)
Newsgroups: comp.ai.philosophy
Subject: Re: Machine learning
Message-ID: <15991@venera.isi.edu>
Date: 11 Dec 90 16:39:40 GMT
References: <4158@dftsrv.gsfc.nasa.gov>
Sender: news@isi.edu
Reply-To: smoliar@vaxa.isi.edu (Stephen Smoliar)
Organization: USC-Information Sciences Institute
Lines: 35

In article <4158@dftsrv.gsfc.nasa.gov> jones@amarna.gsfc.nasa.gov writes:
>  One bad habit which afflicts learning research is the failure to
>distinguish between that which the machine can legitimately learn for itself,
>and that which the human programmers jolly well better program in by hand.

There is an even worse habit which Minsky discusses in THE SOCIETY OF MIND:

		The problem is that we use the single word "learning"
	to cover too diverse a society of ideas.  Such a word can be
	useful in the title of a book, or in the name of an institution.
	But when it comes to studying the subject itself, we need more
	distinctive terms for important, different ways to learn.

Minsky then goes on to propose some of these terms, not all of which I am sure
I agree with;  and I suspect I could think up some more given the time.  The
point is that, like intelligence itself, we assume that anything that can be
captured in a single word can, somehow or another, be implemented in code.
Anything which counts as a result in machine learning has involved results
in a very narrow, highly specific scope.  Unfortunately, rather than trying
to explore the nature of that scope (let alone consider how it might interact
with other, equally narrow scopes), researchers are forever tempted to
advertise their results as advances in "machine learning," a claim which
lends little to our understanding of just what they have achieved.  If we
had less inflation of accomplishment, we might discover that our achievements
are not as weak as they tend to appear.

=========================================================================

USPS:	Stephen Smoliar
	5000 Centinela Avenue  #129
	Los Angeles, California  90066

Internet:  smoliar@vaxa.isi.edu

"It's only words . . . unless they're true."--David Mamet