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Re: Shirky / Syllogisms / Semantic Web

From: Adrian Walker <adrianw@snet.net>
Date: Mon, 24 Nov 2003 13:18:10 -0500
Message-Id: <>
To: Drew McDermott <drew.mcdermott@yale.edu>
Cc: www-rdf-rules@w3.org, www-rdf-interest@w3.org, clay@shirky.com

Drew, Clay --

There are surely two different things going on here:

#1. Can syllogism-style deductive reasoning be useful in the real world?

#2. Is the Semantic Web a "Good Thing" ?

I'll pass on #2, but here are some thoughts about #1.

Yes, reasoning in natural language is very tricky.  To add to Clay's examples:

       a sandwich is better than nothing
       nothing is better than a good square meal
      a sandwich is better than a good square meal             Wrong!

On the other hand, much of our commercial life these days runs on SQL, 
which does -- you guessed it -- deductive reasoning.  So long as it does it 
in an obscure non-English notation, we are happy for it to support our 
economic well being.

So, I'd argue that many of the errors in deductive reasoning, like the ones 
that Clay lists, come from overloading of English sentences in ways that we 
understand but that machines do not understand.  (_We_ know that Nike is 
not a person.  If the machine is set up without enough knowledge/context, 
it does not know this, and it makes comical mistakes)

I'd also argue that we are still a long way from getting machines to use 
English the way that we do, in spite of some heroic research efforts over 
the years.  It's just a very hard problem.

Yet, there does seem to be hope.  I have been advocating a lightweight 
approach to automated reasoning in English,  in which the author of a set 
of deductive rules gets immediate feedback about how they relate to his/her 
cognitive model of the world.  There's a link labeled "Semantic Web 
Presentation" at www.reengineeringllc.com that goes into this in more 
detail.  At the same site, there are also a number of running examples of 
deductive reasoning in something close to English, and you can also write 
and run your own examples.

As Clay points out, discussion around these issues has been going on for 
years, if not centuries.  However, I for one am always intrigued by 
arguments like Clay's, of the general form "you cannot possibly do X with 
Y"   (:-)

                                   Cheers,  -- Adrian

                                            INTERNET BUSINESS LOGIC


Dr. Adrian Walker
Reengineering LLC
PO Box 1412
CT 06011-1412 USA

Phone: USA 860 583 9677
Cell:    USA  860 830 2085
Fax:    USA  860 314 1029

At 09:27 PM 11/23/03 -0500, you wrote:

>Bijan Parsia pointed me in the direction of this anti-Semantic-Web
>article by Clay Shirky:
>     http://www.shirky.com/writings/semantic_syllogism.html
>It's worth reading.  (Full disclosure: He praises an old paper of
>mine; this is not the only reason to read it.)
>The paper argues that deduction (which he calls "syllogism" for no
>reason I can see) is hopelessly inadequate for realistic
>applications.  I half-agree with him.  I think he underestimates the
>need for deductive rules in tasks such as datatype transformations;
>but it's equally true that many of the people involved in the SW are
>overoptimistic about how much mileage can be gotten from deduction in
>supporting things like reasoning about contractual obligations.
>The perennial debate (recently revived on www-rdf-rules@w3.org) about
>the need for negation-as-failure illustrates the point.  Those who
>deny the need for NAF believe that somehow deductive methods will
>arise that can draw conclusions of equivalent use monotonically.
>(Yes, I know that one can view NAF as a simple abbreviation convention
>for inferences that are really deductive, but in practice nonmonotonic
>inference is a device for _escaping_ deduction.)
>Consider the planning algorithms that are an important application of
>OWL-S.  Are they deductive?  Some are, some aren't.  For others it's
>hard to say.  The fact is that computation is a more important
>category for the Semantic Web than deduction -- just as it is
>everywhere else.  It is usually much easier to think about algorithms
>as producing outputs than as producing conclusions.  These outputs
>often achieve status as "conclusions" as a pragmatic postprocessing
>phase.  E.g., a planner's output is taken as a recipe for guiding
>behavior.  The agent using the planner concludes that this is the best
>course of action for it to take.  It may be, but for a self-justifying
>reason: the only planner the agent has couldn't come up with something
>it thought was better.  Another example: Turbotax concludes that you
>owe a certain amount of tax.  Is that a deductive conclusion?
>Possibly.  But it doesn't produce a proof, and it would be rather
>difficult to produce one.  Another: A vision program might conclude
>that you are in the room.  This is clearly not a deductive conclusion.
>Etc., etc.
>It's annoying that Shirky indulges in the usual practice of blaming AI
>for every attempt by someone to tackle a very hard problem.  The
>image, I suppose, is of AI gnomes huddled in Zurich plotting the next
>attempt to --- what? inflict hype on the world?  AI tantalizes people
>all by itself; no gnomes are required.  Researchers in the field try
>as hard as they can to work on narrow problems, with technical
>definitions.  Reading papers by AI people can be a pretty boring
>experience.  Nonetheless, journalists, military funding agencies, and
>recently the World-Wide Web Consortium, are routinely gripped by
>visions of what computers should be able to do with just a tiny
>advance beyond today's technology, and off we go again.  Perhaps
>Mr. Shirky has a proposal for stopping such visions from sweeping
>through the population.
>                                    -- Drew McDermott
>                                       Yale Computer Science Department
Received on Monday, 24 November 2003 13:14:45 UTC

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