Chomskyan
linguistics, as we shall see further on, does not acknowledge any application of
syntax outside the internal realm of mind, semantics being one of the components
of syntax. The primary difficulty in AI work, and that which binds it so closely
with philosophy, cognitive science, psychology, and computational and natural
linguistics, is that in order to build a mind, we must understand that which we
are building. While we understand the external functions which are carried out
by the brain/mind (age old mind/body problem), we do not understand the mind
itself. Therefore we could (though this is exceedingly difficult and has not yet
been done fully) imitate the mind (or language) but not simulate it. That is not
to say that this is impossible in the future, but rather that the current
paradigm must be transcended and an entirely new way of understanding the mind
and machines must be put forth. A computer imitating intelligence would be like
an actor who plays someone smarter than himself, whereas simulation is only
possible where there is a mathematical model, a virtual machine, representing
the system being simulated. Research with the goal of imitation is called weak
AI and that with the goal of simulation is called strong AI. And so, as set
forth by Chomsky, it is the goal of computational linguistics to create a
mathematical model of a native speaker's understanding of his language, as it is
the goal of AI to create a mathematical model of the mind as a whole. This
analogy is imbalanced in that computational linguistics is not a separate
discipline, but rather could very well be the key to AI. In addition, the
relationships between computational linguistics and linguistics, or of AI and
cognitive psychology (or philosophy of mind) are not of dependence of one upon
the other, but of interdependence. If AI researchers were to create a functional
model of the human mind in a machine, this would provide (perhaps
all-encompassing) insight into the nature of the human mind, just as a complete
understanding of the human mind would allow for computational modeling.
The
understanding of the interrelatedness of these fields is essential because in
the end it will most likely be through a synthesis of work in the various fields
that progress will be made. To return to the specifics of computational
linguistics, we see that while Chomsky's work was vastly responsible for
spawning the modern field, the idea of natural language understanding (more on
this below) has been intricately tied to AI since Alan Turing posed his Turing
Test in 1950 (which, incidentally, he predicted would be passed by the year
2000) . This test, which would supposedly determine that a machine had attained
intelligence, is essentially that a computer would be able to converse in a
natural language well enough to convince an interrogator he was talking to a
human being. Yet, as we discussed above, there is a great difference between a
computer so extensively programmed as to be able to imitate linguistic ability
(which in itself has thus far proven extremely difficult if not impossible) or
another conscious cognitive function, and one which simulates it. For example, a
computer voice recognition system (one far more perfected than those available
in the present day) which has advanced pattern-recognition abilities and can
respond to any natural language vocal command with the proper action, still
would not be said to understand language. The true sign of AI would be a
computer who possessed a generative grammar, the ability to learn and to use
language creatively. This possibility may not actually be possible, and Chomsky
would be the first to argue that it wouldn't, yet an examination into his more
recent work in his minimalist program shows some strands of thought whose
implications are far outside of his rationalist heritage, and which could be
important to AI in the future. Attempts at language understanding in computers
before Chomsky were limited to trials like the military-funded effort of Warren
Weaver, who saw Russian as English coded in some strange symbols.
