Artificial Social Intelligence
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A conference on the potential connections between sociology and work in
artificial intelligence was sponsored by the National Science Foundation
and held at the National Center for Supercomputing Applications at the
University of Illinois in May 1993. The Participants were:
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William Sims Bainbridge, NSF Sociology Program
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Edward E. Brent, University of Missouri, Columbia
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Kathleen M. Carley, Carnegie-Mellon University
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David R. Heise, Indiana University
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Michael W. Macy, Brandeis University
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Barry Markovsky, University of Iowa
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John Skvoretz, University of South Carolina
Abstract
Sociologists have begun to explore the gains for theory and research that
might be achieved by artificial intelligence technology: symbolic
processors, expert systems, neural networks, genetic algorithms, and
classifier systems. The first major accomplishments of artificial social
intelligence (ASI) have been in the realm of theory, where these techniques
have inspired new theories as well as helping to render existing theories
more rigorous. Two application areas for which ASI holds great promise are
the sociological analysis of written texts and data retrieval from the
forthcoming Global Information Infrastructure. ASI has already been applied
to some kinds of statistical analysis, but how competitive it will be with
more conventional techniques remains unclear. To take advantage of the
opportunities offered by ASI, sociologists will have to become more computer
literate and will have to reconsider the place of programming and computer
science in the sociological curriculum. ASI may be a revolutionary approach
with the potential to rescue sociology from the doldrums into which some
observers believe it has fallen.
The full text of this report was published in Annual Review of
Sociology in 1994 (vol. 20, pp. 407-436).
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