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The issues presented in this chapter are part of what is usually called the
philosophy
of mind
, an area of research well represented in most departments of philosophy and
in various articles in [59].
This area began more or less with the writings of Rene Descartes (1596-1650),
who wondered how an intangible mind could interact with a physical body (the
so-called mind-body problem). Although there was always a fascination with a vari-
ety of automata, attention shifted decisively to computers as soon as they became
widely known. Turing's paper introducing the Turing Test [66] was perhaps a water-
shed point in this evolution, although he did what he could to stand outside the area
and quell further discussion. Searle's paper on the Chinese Room [64] was another
milestone that resulted in a flurry of replies and commentary, including my own
Summation Room argument [61]. Although the ideas in Searle's paper may seem
frustratingly naive to many computer scientists, they have withstood the test of time.
There are many other aspects of the philosophy of mind that have not even been
touched on here. Among them are the following: Jerry Fodor argues for a “mentalese”
that has many of the properties of natural languages [60]; Daniel Dennett and many
others study properties of consciousness [58]; and there are many who argue that
the human mind cannot be computational, based on considerations such as G odel's
Incompleteness Theorem [62] and even quantum mechanics [63].
But perhaps the most thought-provoking philosophy related to thinking and com-
putation is the work of Brian Cantwell Smith, for example [65]. His writing can
be hard to read and is not about the philosophy of mind at all, but more on the
other side of the street, the
philosophy of computation
. Smith argues (convincingly)
that computation must be understood as more than shuffling around uninterpreted
symbols. His view is that in some cases the interpretation of the symbols matters to
the computation, although in many cases that interpretation is outside the “causal
reach” of the person or computer using the symbols. His attempt to formulate the
approach to knowledge taken in this topic, but taking into account this richer notion
of computation, is what he calls the
knowledge representation hypothesis
(see [1], p. 6).
