Projects involve testing and theoretically extending the Bayesian truth serum (BTS) scoring method.
BTS is a scoring system for eliciting and evaluating subjective opinions from a group of respondents, in situations where the user of the method has no independent means of evaluating respondents’ honesty or their ability. It leverages respondents’ predictions about how other respondents will answer the same questions. Through these predictions, respondents reveal their meta-knowledge, which is knowledge of what other people know.
Current projects apply BTS to artistic judgments, chess, medical diagnoses, and forecasting of political events and developments. Research in the forecasting category is linked to a larger Draper-MIT forecasting project, funded by Intelligence Advanced Research Projects Activity (IARPA), under the Aggregative Contingent Estimation program (ACE).
Key publications
- Prelec, D., Seung, H.S., and McCoy, J. “A solution to the single-question crowd wisdom problem.” Nature, 2017, 541, 532-535.
- Prelec, D. “A Bayesian truth serum for subjective data.” Science, 2004, 306, 462-466.
- Prelec, D. “Introspection and Communication: A Game-Theoretic Approach.” Harvard Business School. April, 1987, 88-032
Works in Progress
- D. Prelec., Bilateral Bayesian truth serum: The n x m signals case.
- Olsson, H., Bruine de Bruin, W., Galesic, M. And D. Prelec. Combining survey questions with a Bayesian bootstrap method yields accurate election forecasts.
- McCoy and Prelec (2017) “A statistical model for aggregating judgments by incorporating peer predictions“ Working Paper
- Hauser, R., Prelec, D., and Mijovic-Prelec, D. (2017) “Self-assessment: Consistency and Effects on Projection.” Working paper.
- Bernardic, U., Prelec, D., and Mijovic-Prelec, D. (2017)“The impact of Oath and Bayesian Truth Serum on Self-Deception.” Working paper.
Other Publications
- Galesic, M., Bruine de Bruin, W., Dalege, J., Feld, S., Kreuter, F., Olsson, H., Prelec, D., Stein, D. L. and T. van der Does. Human social sensing is an untapped resource for social sciences. Nature, 2021, 591(7866), 214-222.
- Cvitanić, J., Prelec, D., Radas, S. and H. Šikić. 2020. Incentive-compatible surveys via posterior probabilities. Theory of Probability & Its Applications, 2020, 65(2), 292-321.
- Cvitanić, J., Prelec, D., Riley, B. and B. Tereick. Honesty by type-matching, American Economic Review: Insights. 2019, 1(2), 179-192.
- Cvitanić, J., Prelec, D., Radas, S., and H. Šikić. Game of Duels: Information-theoretic axiomatization of scoring rules. IEEE Transactions on Information Theory, 2018, 65(1), 530-537.
- Radas, S and D. Prelec, Whose data can we trust: How meta-predictions can be used to uncover credible respondents in surveys. PLOSOne, December 2, 2019.
- Weaver, Ray, and Drazen Prelec. “Creating truth-telling incentives with the Bayesian truth serum.” Journal of Marketing Research 50, no. 3 (2013): 289-302.
- John, L., Loewenstein, G., and D. Prelec. “Measuring the Prevalence of Questionable Research Practices with Incentives for Truth-telling,” Psychological Science (March 2012).
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MIT Sloan Neuroeconomics Lab 