NeurIPS 2021poster16 citations

Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences

Grant Schoenebeck, Biaoshuai Tao

Abstract

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).

information aggregationsocial choicemechanism design
BibTeX
@inproceedings{
schoenebeck2021wisdom,
title={Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences},
author={Grant Schoenebeck and Biaoshuai Tao},
booktitle={Advances in Neural Information Processing Systems},
editor={A. Beygelzimer and Y. Dauphin and P. Liang and J. Wortman Vaughan},
year={2021},
url={https://openreview.net/forum?id=C5jDWzrZak}
}
Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences · NeurIPS 2021