[mod.ai] Taxonomizing in AI and Dumplings

sas@BBN-VAX.ARPA (Seth Steinberg) (02/13/86)

From: Seth Steinberg <sas@BBN-VAX.ARPA>


Building a taxonomy is a means of predicting what will be found. Anyone
who has read any of Steve Gould's columns in Natural History will be
quite familiar with this problem.  When Linnaeus devised the modern
biological taxonomy of the plant kingdom he was criticized for his
heavy emphasis on the sex lives of the flowers.  He was considered
crude and salacious.  He worked in a hurry to preempt any competetive
scheme and avoid a split in the field but his choice was prophetic and
his emphasis on sex was vindicated by Darwin's later work which argued
that sex was both essential to selection (no sex, no children) AND to
the origin and maintenance of the species.

Of course for every "good" taxonomy there are dozens of losers. Take
the old earth, air, fire and water taxonomy with its metaphoric power.
It still works; look in the Science Fiction and Fantasy section of your
local bookstore.  Of course chemists and physicists use Medeleev's
taxonomy of the elements which has much better predictive power. There
is nothing wrong with building these structures as long as they can be
used to predict or explain something.  Breaking up LISP programs into
families based on the number of parentheses has only limited predictive
power.

Building a taxonomy is no more or less than constructing a theory and
building a theory is useful because it gives people an idea of what to
look for.  A sterile taxonomy is not particularly useful.  That is the
positive side.  A theory also tells people what to ignore and biology
is full of overlooked clues, all carefully noted and explained, waiting
to be illuminated by a new theory.

I think the debate going on now is typical in any young field.  If we
had a theory we could use it to march rapidly along its path, much like
an Interstate highway.  Even if we find it doesn't get us where we want
to go, we had a smooth pleasant ride.  Witness classical
electrodynamics, its collapse and the advent of quantum theory.  The
justifiable fear is that we will race past our exit and exclude or
ignore crucial signs which indicate the correct path.

Personally I think that it is time to set up a few theories of AI so
that we can have the fun of knocking them down.  As one might expect
most theories at this stage are either useless and lack predictive
power (except possibly for predicting tenure) or are so weak and full
of holes that you can drive a truck full of LISP machines through them.
When people start developing theories with real predictive power that
are really hard to knock down then we can relax a bit.

						Seth Steinberg

P.S. This month's Scientific American had an article on quantum effects
in biological reactions at low temperatures and the author argues that
conformational resonances (which determine reactivities) are driven by
quantum tunneling!  Maybe there ARE carcinogenic vibrations!