Section 5.1-5.2, on the best of AI x Prediction markets
SBTs could unlock a new class of rich models and experiments in predictive power and relative
expertise. Whereas prediction markets elicit one number—the price of a contract—quadratic polling elicits each participant’s exact belief about the probability of an event. SBTs enable further computation over those beliefs in social context of the education credentials, memberships, and general sociality of a participant to develop better weighted (or non-linearly synthesized) predictive models, likely surfacing expert predictors at novel, unforeseen intersections. So even if a poll did not aggregate beliefs well, polls could be studied retroactively to uncover the characteristics of “more correct” participants and convene better tailored “experts” in future polls, perhaps in a deliberative team context. These mechanisms are closely related to those we advocate throughout this paper. In the same way that quadratic mechanisms discounted by correlation scores can transform poorly coordinated top-down public goods into powerful, bottom-up plural network goods, they can also transform governance systems based on zero-sum prediction markets that incent participants to hide their information (e.g., Futarchy) into more positive-sum plural sense-making that can encourage revelation and synthesis of new and better information.