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Title: Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences
We consider two-alternative elections where voters' preferences depend on a state variable that is not directly observable. Each voter receives a private signal that is correlated to the state variable. As a special case, our model captures the common scenario where voters can be categorized into three types: those who always prefer one alternative, those who always prefer the other, and those contingent voters whose preferences depends on the state. In this setting, even if every voter is a contingent voter, agents voting according to their private information need not result in the adoption of the universally preferred alternative, because the signals can be systematically biased.We present a mechanism that elicits and aggregates the private signals from the voters, and outputs the alternative that is favored by the majority. In particular, voters truthfully reporting their signals forms a strong Bayes Nash equilibrium (where no coalition of voters can deviate and receive a better outcome).  more » « less
Award ID(s):
2007256 1452915
NSF-PAR ID:
10316791
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Advances in Neural Information Processing Systems 34 pre-proceedings (NeurIPS 2021)
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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