我们研究了一个众包问题，该平台旨在激励分布的员工提供高质量和真实的解决方案，但没有能力验证解决方案。虽然之前的研究大多假设平台和员工拥有对称的信息，但我们研究的是一个平台具有信息优势的信息不对称场景。具体来说，平台了解更多关于工人平均溶液精度的信息，并有策略地将这些信息透露给工人。员工将利用宣布的信息来确定他们在努力完成任务时获得奖励的可能性。我们研究了两种类型的工人:完全信任声明的天真工人和基于声明更新先前信念的战略工人。对于天真的工人，我们表明平台应该总是宣布一个高平均精度，以最大化其收益。然而，对于战略工作者来说，这并不总是最优的，因为这可能会降低平台公告的可信度，从而降低平台收益。有趣的是，当面对战略工作者时，该平台甚至可能会宣布平均精度低于实际值。另一个违反直觉的结果是，平台收益可能会减少高精度工人的数量。
原文题目：Strategic Information Revelation in Crowdsourcing Systems Without Verification
原文：We study a crowdsourcing problem where the platform aims to incentivize distributed workers to provide high quality and truthful solutions without the ability to verify the solutions. While most prior work assumes that the platform and workers have symmetric information, we study an asymmetric information scenario where the platform has informational advantages. Specifically, the platform knows more information regarding worker average solution accuracy, and can strategically reveal such information to workers. Workers will utilize the announced information to determine the likelihood that they obtain a reward if exerting effort on the task. We study two types of workers, naive workers who fully trust the announcement, and strategic workers who update prior belief based on the announcement. For naive workers, we show that the platform should always announce a high average accuracy to maximize its payoff. However, this is not always optimal for strategic workers, as it may reduce the credibility of the platform announcement and hence reduce the platform payoff. Interestingly, the platform may have an incentive to even announce an average accuracy lower than the actual value when facing strategic workers. Another counterintuitive result is that the platform payoff may decrease in the number of high accuracy workers.
无验证的众包系统中的战略信息披露.pdf