Social Artificial Intelligence Research Articles

The Social Information Infrastructure

The Division of Social, Behavioral, and Economic Research of the National Science Foundation has explored aggressively the potential involvement of the social sciences in the National Information Infrastructure. We invision the NII as a global network of computer communications, which will evolve out of the Internet, linking all social scientists to massive digital libraries and to myriad smaller distributed data sources containing information of every imaginable sort. Five workshops have charted applications of high-performance computing in the social and behavioral sciences: cognitive science, computational geography, computational economics, artificial social intelligence, and electronic networks. A survey of SBER programs revealed that many are helping to create the information infrastructure, and substantial investment in six "flagship" digital library projects will develop the systems necessary for the NII of the 21st century. Keywords: information infrastructure, digital library, cognitive science, computational geography, computational economics, artificial intelligence, Internet.

Artificial Social Intelligence

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.

Grand Computing Challenges for Sociology

Consideration of four possible grand computing challenges in sociology suggests that progress will come from wholly fresh approaches, rather than from mere improvements in current kinds of social science computing. Although it will be useful to access ordinary libraries over the future universal communications net, placing conventional sociological data sets on it will accomplish little. More valuable would be development of technologies that would allow social scientists far greater access to data already collected by government and industry while protecting the confidentiality of information about individuals. Especially exciting would be automatic systems to read data from hand-written records like the massive historical censuses of the 19th century. In nearly every area of social science, artificial social intelligence has the potential to revolutionize research and theory. Keywords: computing, sociology, networks, government data sets, U.S. census, artificial intelligence.

Artificial Social Intelligence

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.