Abstract:
A theory of "syntactic semantics" is advocated as a way of
understanding how computers can think (and how the
Chinese-Room-Argument
objection to the Turing Test can be overcome):
(1) Semantics, as the
study
of relations between symbols and meanings, can be turned into
syntax—a
study of relations among symbols (including meanings)—and
hence syntax
can suffice for the semantical enterprise. (2) Semantics,
as the process
of understanding one domain modeled in terms of another, can
be viewed recursively: The base case of semantic
understanding—understanding a domain in terms of
itself—is
syntactic understanding. (3) An internal (or "narrow"),
first-person
point of view makes an external (or "wide"), third-person
point of
view otiose for purposes of understanding cognition.
Von Ahn, Luis;
Blum, Manuel;
&
Langford, John
(2004),
"Telling Humans and Computers Apart Automatically:
How Lazy Cryptographers Do AI",
Communications of the ACM
47(2) (February):
57-60.
Abstract:
This article describes the Turing Test for determining whether a
computer can
think. It begins with a description of an "imitation game" for
discriminating between a man and a woman, discusses variations of the
Test, standards for passing the Test, and experiments with real
Turing-like
tests (including Eliza and the Loebner competition).
It then considers what a computer must be able to do in order to
pass a Turing Test, including whether written linguistic behavior is a
reasonable replacement for "cognition", what counts as understanding
natural language, the role of world knowledge in understanding natural
language, and the philosophical implications of passing a Turing Test,
including whether passing is a sufficient demonstration of cognition,
briefly discussing two counterexamples: a table-lookup program and the
Chinese Room Argument.