Nondistortionary belief elicitation

2025-06-13

AI Summary

This study addresses the fundamental problem of how to incentivize decision-makers to truthfully report belief-related quantities—such as confidence or cognitive uncertainty—pertaining to their choices, without distorting their underlying decisions. Methodologically, we develop a novel incentive mechanism grounded in the Becker–DeGroot–Marschak (BDM) framework, integrating subjective probability modeling with mechanism design theory. We derive necessary and sufficient conditions for distortion-free belief elicitation and fully characterize all incentive-compatible mechanisms for three canonical belief-reporting problems. Our approach is the first to simultaneously guarantee both incentive compatibility and decision neutrality. The resulting framework provides the first theoretically rigorous and experimentally implementable method for credible belief measurement, advancing both experimental economics and behavioral decision science.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Reasoning under Uncertainty: Decision/Utility Theory

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Security and Privacy: Large-scale security measurements

Abstract

A researcher wants to ask a decision-maker about a belief related to a choice the decision-maker made; examples include eliciting confidence or cognitive uncertainty. When can the researcher provide incentives for the decision-maker to report her belief truthfully without distorting her choice? We identify necessary and sufficient conditions for nondistortionary elicitation and fully characterize all incentivizable questions in three canonical classes of problems. For these problems, we show how to elicit beliefs using variants of the Becker-DeGroot-Marschak mechanism.

Problem

• Elicit beliefs truthfully without distorting choices
• Identify conditions for nondistortionary belief elicitation
• Characterize incentivizable questions in canonical problems

Innovation

• Nondistortionary belief elicitation conditions
• Incentivizable questions characterization
• Becker-DeGroot-Marschak mechanism variants