Improving Information from Manipulable Data
研究了当决策依赖数据时，数据提供者会操纵数据以影响分配，导致信息损失；提出决策者应承诺低效利用数据来减少信息损失、提高分配准确性。
Abstract Data-based decision making must account for the manipulation of data by agents who are aware of how decisions are being made and want to affect their allocations. We study a framework in which, due to such manipulation, data become less informative when decisions depend more strongly on data. We formalize why and how a decision maker should commit to underutilizing data. Doing so attenuates information loss and thereby improves allocation accuracy.