论文标题
声誉代理：在演出市场提示公平评论
Reputation Agent: Prompting Fair Reviews in Gig Markets
论文作者
论文摘要
我们的研究提出了一种新工具，即声誉代理，以促进演出市场上请求者（雇主或客户）的更公正的评论。当请求者考虑在工人控制之外的因素时，创建的不公平评论会陷入困境的工作人员，并可能导致工作机会损失，甚至从市场上终止。我们的工具利用机器学习来实施一个智能界面，该界面：（1）使用深度学习来自动检测个人何时将不公平的因素包括在她的审查中（工人的控制之外的因素是按市场政策控制的）； （2）提示个人是否纳入了不公平的因素，请重新考虑她的审查。为了研究信誉剂的有效性，我们在不同的演出市场上进行了对照实验。我们的实验表明，与传统方法相比，在整个市场中，声誉代理人都激发了请求者更公平地审查演出工人的表现。我们讨论如何为雇主提供更多关于演出市场政策的工具可以帮助建立同理心，从而导致围绕这些界面产生的工人的潜在不公正现象进行合理的讨论。我们的愿景是，借助促进真理和透明度的工具，我们可以为演出工人带来更公平的待遇。
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.
