Intelligence does not arise only in individual brains; it also arises in groups of individuals. This is collective intelligence: groups of individuals acting collectively in ways that seem intelligent. In recent years, a new kind of collective intelligence has emerged: interconnected groups of people and computers, collectively doing intelligent things. Today these groups are engaged in tasks that range from writing software to predicting the results of presidential elections. This volume reports on the latest research in the study of collective intelligence, laying out a shared set of research challenges from a variety of disciplinary and methodological perspectives. Taken together, these essays -- by leading researchers from such fields as computer science, biology, economics, and psychology -- lay the foundation for a new multidisciplinary field. Each essay describes the work on collective intelligence in a particular discipline -- for example, economics and the study of markets; biology and research on emergent behavior in ant colonies; human-computer interaction and artificial intelligence; and cognitive psychology and the "wisdom of crowds" effect. Other areas in social science covered include social psychology, organizational theory, law, and communications. ContributorsEytan Adar, Ishani Aggarwal, Yochai Benkler, Michael S. Bernstein, Jeffrey P. Bigham, Jonathan Bragg, Deborah M. Gordon, Benjamin Mako Hill, Christopher H. Lin, Andrew W. Lo, Thomas W. Malone, Mausam, Brent Miller, Aaron Shaw, Mark Steyvers, Daniel S. Weld, Anita Williams Woolley
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Thomas W. Malone is Patrick J. McGovern Professor of Management at MIT's Sloan School of Management and Director of the MIT Center for Collective Intelligence. Michael S. Bernstein is Assistant Professor of Computer Science at Stanford University. Thomas W. Malone is Patrick J. McGovern Professor of Management at MIT's Sloan School of Management and Director of the MIT Center for Collective Intelligence. Michael S. Bernstein is Assistant Professor of Computer Science at Stanford University. Daniel S. Weld is Assistant Professor of Computer Science and Engineering at the University of Washington.
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