Truth and Truthfulness: Experimental Tests of the Bayesian Truth Serum

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The proposal objective is to experimentally test and theoretically extend the "Bayesian Truth Serum", a new method for obtaining superior quality information from respondents in opinion research or expert judgment settings. The method rests on a mathematical scoring algorithm that gives respondents an incentive to provide truthful and carefully considered answers to questions, even though only the respondent knows which answer best matches to their truthful opinion. The method could be used to collect truthful expert forecasts of events in the far future (e.g., whether mankind will survive past year 2100), truthful expression of personal tastes or intentions (e.g., intentions to vote), and truthful self-reports of personal behaviors and characteristics (e.g., risky sexual practices).The main idea behind the scoring algorithm is to give high scores to answers that are more common than predicted, with predictions generated by the same respondents who answer the questions. It follows from Bayesian reasoning that truth-telling maximizes expected score even for a respondent who is sure that their truthful opinion represents a minority view. Furthermore, in situations where there is a single objectively correct answer to a question (i.e., a question dealing with objective knowledge), the scoring algorithm should be able to identify the objectively correct answer even if the majority of respondents endorse a different, incorrect answer.