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Collective Intelligence

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. 

  • photo of Jacob Andreas
    X Consortium Career Development Assistant Professor, Department of Electrical Engineering and Computer Science
    Computer Science and Artificial Intelligence Laboratory
    • Natural Language Processing
    • Machine Learning
  • Aleksander Madry photo (Lillie Paquette)
    Professor, Department of Electrical Engineering and Computer Science
    Director, MIT Center for Deployable Machine Learning
    Computer Science and Artificial Intelligence Laboratory
    • Machine Learning
  • Photo of Evelina Fedorenko
    Middleton Career Development Associate Professor of Neuroscience, Department of Brain and Cognitive Sciences
    Investigator, McGovern Institute for Brain Research
    • Natural Language Processing
  • Asu Ozdaglar
    Deputy Dean of Academics, MIT Schwarzman College of Computing
    Professor and Head, Department of Electrical Engineering and Computer Science
    • Machine Learning
  • Daniela Rus portrait
    Deputy Dean of Research, MIT Schwarzman College of Computing
    Director, Computer Science and Artificial Intelligence Laboratory
    Andrew and Erna Viterbi Professor, Department of Electrical Engineering and Computer Science
    • Machine Learning
    • AI Robotics
  • David Rand
    Erwin H. Schell Professor, MIT Sloan School of Management
    Associate Professor, Department of Brain and Cognitive Sciences
    Institute for Data, Systems, and Society
    • Computational Cognition
    • Behavioral Science
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