His method of
computer translation relied on automatic dictionary and grammar reference to
rearrange the word equivalents. But, as Chomsky made very clear, language syntax
is much more than lexicon and grammatical word order, and Weaver's translations
were profoundly inaccurate. Contrary to their original speculations in the dawn
of the AI age (50's-60's), the most complex human capabilities have proven
simple for machines, while the simplest things human children do almost
mindlessly, such as tying shoes, acquiring language, or learning itself, prove
the most difficult (if not impossible). Numerous computer language modeling
programs have been created, the details of which are not essential to the topic
of this paper and will not be delved into, yet none as of yet can approach the
Turing Test. Much difficulty arises from linguistic anomalies like the
ambiguities mentioned above, as in the old AI adage time flies like an arrow;
fruit flies like a banana. The early language programs, like Joseph Weizenbaum's
ELIZA (which was able to convince adult human beings that they were receiving
genuine psychotherapy through a cleverly designed Rogerian system of asking
leading questions and rephrasing important bits of entered data) had nothing to
do with modeling of language. Rather, these were programs which were programmed
to respond to input with a variable output of designed speech with no generative
grammatical or lexical capability. Early attempts at computational linguistics,
under Chomsky's influence, attempted to model sentences by syntax alone, hoping
that if this worked, the semantics could be worked out subsequently, and only
once, for the deep structure. However, as Chomsky showed much later on,
semantics is part of syntax (the most important part), and thereby could not be
dealt with post-syntactically. Not unsurprisingly, the only linguistic area
where computers thus far have shown considerable ability is the area that humans
find the most difficult, whereas the simplest human linguistic abilities remain
elusive. Sentences known as recursive, or left or right-branching such as The
monkey that the lion who had eaten the zebra wouldn't eat ate the banana, have
an infinite capacity for embeddings, allowing for the vastly superior memory of
the computer to be more effective in parsing them.
Understanding that Chomsky's
original breakthroughs (those of Syntactic Structures and his 60's work) had
profound impact on Artificial Intelligence, the remainder of this paper will
speculate on the potential impact of his minimalist program and the nature of
what I will call the syntactic mind. The premise of the argument is presented by SUNY Professor William Rapaport in his essay How to Pass a Turing Test:
Syntactic Semantics, Natural Language Understanding, and First Person Cognition,
as a rebuttal to John Searle's Chinese Room argument, which Rapaport describes
as: 1) Computer programs are purely syntactic. 2) Cognition is semantic. 3)
Syntax alone is not sufficient for semantics. 4) Therefore, no purely syntactic
computer program can exhibit semantic cognition. Rapaport responds by saying
that syntax is sufficient for semantics, and if you accept that, then you
discover that a purely syntactic computer program can exhibit semantic
cognition; in other words, if semantics can be incorporated into syntax, then
the computer program can simulate the cognitive mind. This is a bold statement,
so let's see how it is derived from Chomsky's work. Syntax is defined as the
relations among a set of markers (Rapaport refrains from calling them symbols as
symbol implies an inherent connection to an external object), and semantics is
the relations between the system of markers and other things, (their meanings).
His argument claims that if the set of markers is merged with the set of
meanings, then the resulting set is a new set of markers, a sort of meta-syntax.
The mechanism that the symbol-user (native speaker) uses to understand the
relation between the old and new markers is a syntactic one. The simplest way to
put all this would be that semantics must be understood syntactically, and is
therefore a form of syntax. The crux of the argument is that a word (for example
tree) does not signify an actual external tree-object, but rather signifies the
internal representation tree found in the mind. This idea goes to back to
Chomsky's Lectures on Government and Binding where he introduces Relation R,
elucidated by James McGilvray as reference, but without the idea that reference
relates an LF [Logical Form, or SEM, semantic form] that stands between elements
of an LF and these stipulated semantic values that serve to 'interpret it'.
