Vidal's libraryTitle: | Artificial Social Intelligence |
Author: | William Sims Bainbridge, Edward E. Brent, Kathleen M. Carley, David R. Heise, Michael W. Macy, Barry Markovsky, and John Skvoretz |
Journal: | Annual Review of Sociology |
Volume: | 20 |
Pages: | 407--436 |
Year: | 1994 |
DOI: | 10.1146/annurev.so.20.080194.002203 |
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 artifical 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 techiques remains unclear. To take advantage of the opporunities offere by ADI, sociologists will have to become more computer literate and will have to reconsider the place of programming and computer science in the sociological curriculum. ADI may be a revolutionary approach with the potential to rescue sociology from the doldrums unto which some observersbelieve it has fallen |
Cited by 27 - Google Scholar
@Article{bainbridge94a,
author = {William Sims Bainbridge and Edward E. Brent and
Kathleen M. Carley and David R. Heise and Michael
W. Macy and Barry Markovsky and John Skvoretz},
title = {Artificial Social Intelligence},
googleid = {RfB9Koe4_3EJ:scholar.google.com/},
journal = {Annual Review of Sociology},
year = 1994,
volume = 20,
pages = {407--436},
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 artifical 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 techiques remains unclear. To
take advantage of the opporunities offere by ADI,
sociologists will have to become more computer
literate and will have to reconsider the place of
programming and computer science in the sociological
curriculum. ADI may be a revolutionary approach with
the potential to rescue sociology from the doldrums
unto which some observersbelieve it has fallen},
keywords = {ai sociology},
doi = {10.1146/annurev.so.20.080194.002203},
url = {http://jmvidal.cse.sc.edu/library/bainbridge94a.pdf},
cluster = {8214487136020066373}
}
Last modified: Wed Mar 9 10:13:56 EST 2011