Description
This Mission approaches how we can optimize human-AI group decision making. How can we create super-intelligent groups that operate effectively in dynamic environments? How can highly polarized groups make decisions the whole group will implement?
Goals include defining benchmarks to determine what is superintelligence and character types of tasks and groups, and how to evaluate performance of different types of groups and tasks. Engineering goals include developing modeling and CAD tools for group design, create a library of group configurations, and establish predictive models to evaluate performance.
During Advances in the quest to understand intelligence, a one-day conference held at MIT on Nov. 4, 2022, Tom Malone gave an overview of this Mission and its goals.
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Patrick J. McGovern Professor, MIT Sloan School of ManagementFounding Director, MIT Center for Collective IntelligenceMissions -
Douglas Drane Career Development Professor in Information Technology, MIT Sloan School of Management.Assistant Professor, Information Technology, MIT Sloan School of Management.Missions -
Professor, MIT Sloan School of ManagementAssociate Professor, Department of Brain and Cognitive SciencesInstitute for Data, Systems, and Society- Computational Cognition
- Behavioral Science
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Deputy Dean of Research, MIT Schwarzman College of ComputingDirector, Computer Science and Artificial Intelligence LaboratoryAndrew and Erna Viterbi Professor, Department of Electrical Engineering and Computer Science- Machine Learning
- AI Robotics
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Brit (1961) and Alex (1949) d'Arbeloff Career Development Professor in Engineering Design- Machine Learning
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Mitsui Professor of Political Science, MIT Department of Political ScienceDirector of the MIT Political Experiments Research Lab (PERL)Missions -
Richard S. Leghorn (1939) Career Development Professor at the MIT Sloan School of ManagementFaculty Research Fellow at the NBERMissions