Incentive-Compatible Machine Learning (NSF CCF-0915016)

2016
Chen, Yiling, Stephen Chong, Ian A. Kash, Tal Moran, and Salil P. Vadhan. “Truthful mechanisms for agents that value privacy.” ACM Transactions on Economics and Computation 4, no. 3 (2016). Publisher's VersionAbstract

Version History: Special issue on EC ‘13. Preliminary version at arXiv:1111.5472 [cs.GT] (Nov. 2011).

Recent work has constructed economic mechanisms that are both truthful and differentially private. In these mechanisms, privacy is treated separately from truthfulness; it is not incorporated in players’ utility functions (and doing so has been shown to lead to nontruthfulness in some cases). In this work, we propose a new, general way of modeling privacy in players’ utility functions. Specifically, we only assume that if an outcome $${o}$$ has the property that any report of player $${i}$$ would have led to $${o}$$ with approximately the same probability, then $${o}$$ has a small privacy cost to player $${i}$$. We give three mechanisms that are truthful with respect to our modeling of privacy: for an election between two candidates, for a discrete version of the facility location problem, and for a general social choice problem with discrete utilities (via a VCG-like mechanism). As the number $${n}$$ of players increases, the social welfare achieved by our mechanisms approaches optimal (as a fraction of $${n}$$).

Chen, Yiling, Stephen Chong, Ian A. Kash, Tal Moran, and Salil P. Vadhan. “Truthful mechanisms for agents that value privacy.ACM Transactions on Economics and Computation 4, no. 3 (2016). Publisher's VersionAbstract
Recent work has constructed economic mechanisms that are both truthful and differentially private. In these mechanisms, privacy is treated separately from truthfulness; it is not incorporated in players’ utility functions (and doing so has been shown to lead to nontruthfulness in some cases). In this work, we propose a new, general way of modeling privacy in players’ utility functions. Specifically, we only assume that if an outcome o has the property that any report of player i would have led to o with approximately the same probability, then o has a small privacy cost to player i. We give three mechanisms that are truthful with respect to our modeling of privacy: for an election between two candidates, for a discrete version of the facility location problem, and for a general social choice problem with discrete utilities (via a VCG-like mechanism). As the number n of players increases, the social welfare achieved by our mechanisms approaches optimal (as a fraction of n). Preliminary version on arXiv (2011).