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.