声誉代理：在Gig市场中维护公平评论
Reputation Agent: Prompting Fair Reviews in Gig Markets
摘要：
我们的研究提出了一个新的工具，声誉代理，以促进更公平的评论，从请求者（雇主或客户）的演出市场。当请求者考虑员工无法控制的因素时，就会产生不公平的评论，众所周知，这会困扰临时工，并可能导致失去工作机会，甚至被市场解雇。我们的工具利用机器学习来实现一个智能界面：（1）使用深度学习来自动检测个人何时将不公平因素纳入其审查（根据市场政策，工人无法控制的因素）;（2）如果个人纳入了不公平因素，则提示个人重新考虑其审查。为了研究声誉代理的有效性，我们在不同的演出市场进行了一个对照实验。我们的实验表明，在整个市场，声誉代理，与传统的方法相比，激励请求者更公平地审查零工的表现。我们讨论了为雇主带来更多关于零工市场政策的透明度的工具如何帮助建立同理心，从而围绕这些界面产生的对工人的潜在不公正进行合理的讨论。我们的愿景是，通过促进真相和透明度的工具，我们可以为零工工人带来更公平的待遇。
英文摘要：
Our study presents a new tool, Reputation Agent, to promote fairer reviews from requesters (employers or customers) on gig markets. Unfair reviews, created when requesters consider factors outside of a worker's control, are known to plague gig workers and can result in lost job opportunities and even termination from the marketplace. Our tool leverages machine learning to implement an intelligent interface that: (1) uses deep learning to automatically detect when an individual has included unfair factors into her review (factors outside the worker's control per the policies of the market); and (2) prompts the individual to reconsider her review if she has incorporated unfair factors. To study the effectiveness of Reputation Agent, we conducted a controlled experiment over different gig markets. Our experiment illustrates that across markets, Reputation Agent, in contrast with traditional approaches, motivates requesters to review gig workers' performance more fairly. We discuss how tools that bring more transparency to employers about the policies of a gig market can help build empathy thus resulting in reasoned discussions around potential injustices towards workers generated by these interfaces. Our vision is that with tools that promote truth and transparency we can bring fairer treatment to gig workers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
