Humanist Discussion Group, Vol. 16, No. 23.
Centre for Computing in the Humanities, King's College London
<http://www.princeton.edu/~mccarty/humanist/>
<http://www.kcl.ac.uk/humanities/cch/humanist/>
Date: Tue, 14 May 2002 06:14:11 +0100
From: Willard McCarty <w.mccarty@btinternet.com>
Subject: kinships and differences
A book for the attention of anyone interested in our disciplinary kinships:
The Boundaries of Humanity: Humans, Animals, Machines. James J. Sheehan and
Morton Sosna, eds. Berkeley: University of California Press, 1991. This
collection of essays is based on the papers given at a conference at
Stanford University in April 1987 under the auspices of the Stanford
Humanities Center <http://shc.stanford.edu/> (which also once published the
fine journal, Stanford Humanities Review
<http://www.stanford.edu/group/SHR/>, now defunct).
In the Boundaries volume the most obviously relevant essays are those in
Part II, Humans and Machines, esp. Allen Newell, "Metaphors for Mind,
Theories of Mind: Should the Humanities Mind?"; Terry Winograd, "Thinking
Machines: Can there be? Are we?" (reprinted in D. Partridge and Y. Wilks,
The Foundations of Artificial Intelligence, Cambridge: Cambridge Univ.
Press, 1990, pp. 167-189); Sherry Turkle, "Romantic Reactions: Paradoxical
Responses to the Computer Presence"; Stuart Hampshire, "Biology, Machines,
and Humanity". Of those the essays by Newell and Winograd come close to
*required* reading for us -- and make a very interesting contrast of
attitudes within the AI community of which we must be aware.
Winograd is an important ally, as the book he did with Fernando Flores,
Understanding Computers and Cognition, demonstrates. In this piece he
recognizes the grains of truth from both sides, from the futurologists
proclaiming the dawn of machina sapiens and from the critics pointing to
"the vain pretensions of those who seek to understand mind as computation".
Then he finds the much more complex and interesting picture these grains
lead us to.
Newell's learned arrogance and very interesting rhetorical moves are also
worth close study. These moves are typical of the genre of pronouncements
ex cathedra to non-specialists: (1) dismissal of a set of questions, kind
of knowledge or area of study as unimportant, irrelevant etc.; (2) deferral
of a promised fulfilment, or what Jerry Pournelle used to call the "Real
Soon Now" strategy. By the first he relegates metaphor to the realm of the
literary, i.e. subjective and decorative, so that computation as a
"metaphor for mind" can be dismissed as essentially meaningless, in favour
of a contrastingly scientific "theory of mind". A sideswipe at science
studies, with reference only to Latour and Woolgar, is supposed to restore
the notion of clean, unproblematic objectivity to science. From there it's
a relatively short step to diagrams of cognitive processes as these are
implemented in a system he is working on -- to which, of course, none of us
have access. What he says about the system and the research strategy for
understanding mind is indeed very interesting, but the unexamined notion of
"theory" in relation to this kind of work undermines its value. Better, I
would think, to call it a "model of mind", i.e. roughly, a useful,
tractable fiction employed as a heuristic convenience. The deferral of
promise is more subtle than in the early days, for example in the article
he did with Herbert Simon, "Heuristic Problem Solving: The Next Advance in
Operations Research", Operations Research 6.1 (Jan-Feb 1958): 1-10 -- the
article is in JSTOR. I quote:
"We are now poised for a great advance that will bring the digital computer
and the tools of mathematics and the behavioural sciences to bear on the
very core of managerial activity--on the exercise of judgment and
intuition; on the process of making complex decisions.... Even while
operations research is solving well-structured problems, fundamental
research is dissolving the mystery of how humans solve ill-structured
problems. Moreover, we have begun to learn how to use computers to solve
these problems.... And we now know, at least in a limited area, not only
how to program computers to perform such problem-solving activities
successfully; we also know how to program computers to *learn* to do these
things.... Intuition, insight, and learning are no longer exclusive
possessions of humans: any large high-speed computer can be programmed to
exhibit them also." (p 6)
A number of predictions follow: that within the next 10 years (they
specifically set the date at 1 January 1968), a computer "will be the
world's chess champion... will discover and prove an important new
mathematical theorem... will write music that will be accepted by critics
as possessing considerable aesthetic value... [and that] most theories in
psychology will take the form of computer programs, or of qualitative
statements about the characteristics of such programs" (pp. 7-8). I also
direct your attention to their reply to criticisms in Operations Research
6.3, pp. 449-50, which digs the hole deeper still. A year before the set
date, Marvin Minsky (the brain-is-a-meat-machine man), in Computation:
Finite and Infinite Machines (1967), said somewhat more cautiously that
fulfilment would happen quite soon.
Given Simon and Newell's pioneering work, which (if I am not wrong) began
in managerial science, Terry Winograd's observation at the beginning of his
article, made about 20 years after Simon and Newell's line in the sands of
time, has a particularly accurate bite: "Indeed, artificial intelligence
has not achieved creativity, insight and judgment. But its shortcomings are
far more mundane: we have not yet been able to construct a machine with
even a modicum of common sense or one that can converse on everyday topics
in ordinary language.... '[A]rtificial intelligence' ... can usefully be
likened to bureaucracy in its rigidity, obtuseness, and inability to adapt
to changing circumstances. The weakness comes not from insufficient
development of the technology but from the inadequacy of the basic tenets"
(pp 198-9) -- by which he means essentially philosophical tenets that
largely still prevail. One is reminded of John F Sowa's statement in
Knowledge Representation: Logical, Philosophical, and Computational
Foundations (2000): "Perhaps there are some kinds of knowledge that cannot
be expressed in logic." (p. 12).
Michael Williams' point, in Problems of Knowledge (2001), is worth
recalling: "Demarcational projects use epistemological criteria to sort
areas of discourse into factual and non-factual, truth-seeking and merely
expressive, and, at the extreme, meaningful and meaningless. Such projects
amount to proposals for a map of culture: a guide to what forms of
discourse are 'serious' and what are not. Disputes about demarcation... are
disputes about that shape of our culture and so, in the end, of our lives"
(p. 12).
The debate is ongoing and important, and as it goes on it gets, as Winograd
says, more complex. Putting our debate about computing into the broader
context of humans, animals and machines shows us just how important it is.
Comments?
Yours,
WM
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