论文标题
成为超级土耳其人:通过高收入工人的策略提高工资
Becoming the Super Turker: Increasing Wages via a Strategy from High Earning Workers
论文作者
论文摘要
传统上,人群市场没有提供有关公平支付的任务或哪些请求者不可靠的透明度信息,从而有限。研究人员认为,人群工人获得低工资的关键原因是由于缺乏透明度。结果,已经开发了工具来在人群市场中提供更多的透明度来帮助工人。但是,尽管大多数工人都使用这些工具,但他们的收入仍然低于最低工资。我们认为缺少的元素是有关如何使用透明度信息的指导。在本文中,我们探讨了新手工人如何通过遵循超级土耳其人的透明度标准,即在亚马逊机械土耳其人(MTURK)上获得更高工资的人群。我们认为,超级土耳其人已经开发了使用透明度信息的有效过程。因此,通过让新手遵循超级土耳其人的标准(在超级土耳其人中很简单且受欢迎),我们可以帮助新手提高工资。为此,我们:(i)进行了调查和数据分析,以在计算上确定超级土耳其人用于处理透明工具的简单但常见的标准; (ii)针对新手进行了为期两周的现场实验,他们遵循了这一超级土耳其语标准,以在MTURK上找到更好的工作。我们研究中的新手查看了1,394个请求者的25,000多个任务。我们发现,利用这一超级土耳其人标准的新手比其他新手获得了更好的工资。我们的结果强调,应将支持人群工人的工具开发与教育机会配对,以教工人如何有效地使用工具及其相关指标(例如透明度值)。我们将提出设计建议,以授权群众工人赚取更高的薪水。
Crowd markets have traditionally limited workers by not providing transparency information concerning which tasks pay fairly or which requesters are unreliable. Researchers believe that a key reason why crowd workers earn low wages is due to this lack of transparency. As a result, tools have been developed to provide more transparency within crowd markets to help workers. However, while most workers use these tools, they still earn less than minimum wage. We argue that the missing element is guidance on how to use transparency information. In this paper, we explore how novice workers can improve their earnings by following the transparency criteria of Super Turkers, i.e., crowd workers who earn higher salaries on Amazon Mechanical Turk (MTurk). We believe that Super Turkers have developed effective processes for using transparency information. Therefore, by having novices follow a Super Turker criteria (one that is simple and popular among Super Turkers), we can help novices increase their wages. For this purpose, we: (i) conducted a survey and data analysis to computationally identify a simple yet common criteria that Super Turkers use for handling transparency tools; (ii) deployed a two-week field experiment with novices who followed this Super Turker criteria to find better work on MTurk. Novices in our study viewed over 25,000 tasks by 1,394 requesters. We found that novices who utilized this Super Turkers' criteria earned better wages than other novices. Our results highlight that tool development to support crowd workers should be paired with educational opportunities that teach workers how to effectively use the tools and their related metrics (e.g., transparency values). We finish with design recommendations for empowering crowd workers to earn higher salaries.