Free-Riding in Multi-Issue Decisions
Abstract
Voting in multi-issue domains allows for compromise outcomes that satisfy all voters to some extent. Such fairness considerations, however, open the possibility of a special form of manipulation: free-riding. By untruthfully opposing a popular opinion in one issue, voters can receive increased consideration in other issues. We study under which conditions this is possible and show that even weak fairness considerations enable free-riding. Additionally, we study free-riding from a computational and experimental point of view. Our results show that free-riding in multi-issue domains is often possible, but comes at a non-negligible individual risk for voters. Thus, the allure of free-riding is smaller than one could intuitively assume.
Fields of Study & Subjects
Experimental Behavioral Economics Studies
Game Theory and Voting Systems
Auction Theory and Applications
Publication details
- Journal / source
- Journal of Artificial Intelligence Research
- Publisher
- AI Access Foundation
- Volume
- 86
- Publication date
- 29 July 2026
- Language
- EN