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

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).

Cite

Text

Schoenebeck and Tao. "Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences." Neural Information Processing Systems, 2021.

Markdown

[Schoenebeck and Tao. "Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences." Neural Information Processing Systems, 2021.](https://mlanthology.org/neurips/2021/schoenebeck2021neurips-wisdom/)

BibTeX

@inproceedings{schoenebeck2021neurips-wisdom,
  title     = {{Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences}},
  author    = {Schoenebeck, Grant and Tao, Biaoshuai},
  booktitle = {Neural Information Processing Systems},
  year      = {2021},
  url       = {https://mlanthology.org/neurips/2021/schoenebeck2021neurips-wisdom/}
}