GKMARH@IRISHMVS.BITNET (steven horst 219-289-9067) (07/26/88)
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Date: Fri, 22 Jul 88 17:39 EDT
To: ailist@ai.ai.mit.edu
From: steven horst 219-289-9067 <GKMARH%IRISHMVS.BITNET@MITVMA.MIT.EDU>
Subject: Turing machines and brains (long)
I don't recall how the discussion of Turing machines and their
suitability for "imitating" brains started in recent editions of
the Digest, but perhaps the following considerations may prove
useful to someone.
I think that you can go a long way towards answering the question
of whether Turing machines can "imitate" brains or minds by rephrasing
the question in ways that make the right sorts of distinctions.
There have been a number of attempts to provide more perspicuous
terminology for modeling/simulation/duplication of mental
processes, brains -- or for that matter any other sorts of objects,
systems or processes. (I'll use "system" as a general term for things
one might want to model.) Unfortunately, none of these attempts
at supplying a technical usage has become standard. (Though personally
I am partial to the one Martin Ringle uses in his anthology of
articles on AI.)
The GENERAL question, however, seems to be something like this:
WHAT FEATURES CAN COMPUTERS (or programs, or computers running programs,
it really doesn't matter from the perspective of functional
description) HAVE IN COMMON WITH OTHER OBJECTS, SYSTEMS AND PROCESSES?
Of course some of these properties are not relevant to projects of
modeling, simulation or creation of intelligent artifacts. (The fact
that human brains and Apple Macintoshes running AI programs both exist
on the planet Earth, for example, is of little theoretical interest.)
A second class of similarities (and differences) may or may not be
relevant, depending on one's own research interests. The fact that
you cannot build a universal Turing machine (because it would require
an infinite storage tape) is irrelevant to the mathematician, but
for anyone interested in fast simulations, it is important to have
a machine that is able to do the relevant processing quickly and
efficiently. So it might be the case that a Turing machine could
run a simulation of some brain process that was suitably accurate,
but intolerably slow.
But the really interesting questions (from the philosophical
standpoint) are about (1) what it is, in general, for a program to
count as a model of some system S, and (2) what kinds of features
Turing machines (or other computers) and brains can share. And I
think that the general answer to these questions goes something like
this: what a successful model M has in common with the system S of
which it is a model is an abstract (mathematical) form. What, after
all, does one do in modeling? One examines a system S, and attempts
to analyze it into constituent parts and rules that govern the
interactions of those parts. One then develops a program and data
structures in such a manner that every unit in the system modeled
has a corresponding unit in the model, and the state changes of
the system modeled are "tracked" by the state changes of the model.
The ideal of modeling is isomorphism between the model and the
system modeled. But of course models are never that exact, because
the very process of abstraction that yields a general theory
requires one to treat some factors as "given" or "constant" which
are not negligible in the real world.
With respect to brains and Turing machines, it might be helpful
to ask questions in the following order:
(1) What brain phenomena are you interested in studying?
(2) Can these phenomena be described by lawlike generalizations?
(3) Can a Turing machine function in a manner truly isomorphic
to the way the brain phenomenon functions? (I take it that
for many real world processes, such ideal modeling cannot be
accomplished, because to but it crudely, most of reality
is not digital.)
(4) Can a Turing machine function in a manner close enough to being
isomorphic with the way the brain processes function so as to
useful for your research project? (Whatever it may be....)
(5) Just what is the relationship between corresponding parts of
the model and the system modeled? Most notably, is functional
isomorphism the only relevant similarity beween model and
system modeled, or do they have some stronger relationships
as well- e.g., do they respond to the same kinds of input
and produce the same kinds of output?
What is interesting from the brain theorist's point of view, I should
think, is the abstract description that program and brain process
share. The computer is just a convenient way of trying to get at that
and testing it. Of course some people think that minds or brains
share features with (digital) computers at some lower level as well,
but that question is best kept separate from the questions about
modeling and simulation.
Sorry this has been so long. I hope it proves relevant to
somebody's interests.
Steven Horst
BITNET address....gkmarh@irishmvs
SURFACE MAIL......Department of Philosophy
Notre Dame, IN 46556