From prediction markets to interpretable collective intelligence

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Publication date: 28 April 2022

Abstract: We outline how to create a mechanism that provides an optimal way to elicit, from an arbitrary group of experts, the probability of the truth of an arbitrary logical proposition together with collective information that has an explicit form and interprets this probability. Namely, we provide strong arguments for the possibility of the development of a self-resolving prediction market with play money that incentivizes direct information exchange between experts. Such a system could, in particular, motivate experts from all over the world to collectively solve scientific or medical problems in a very efficient manner. In our main considerations about real experts, they are not assumed to be Bayesian and their behavior is described by utilities that satisfy the von Neumann--Morgenstern axioms only locally.

Has companion code repository: https://github.com/nicknick85/collective-intelligence-research

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