Crowdsourcing as a Tool for Research: Methodological, Fair, and Political Considerations

Q2 Arts and Humanities
Stephen C. Rea, Hanzelle Kleeman, Qin Zhu, Benjamin Gilbert, Chuan Yue
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引用次数: 5

Abstract

Crowdsourcing platforms are powerful tools for academic researchers. Proponents claim that crowdsourcing helps researchers quickly and affordably recruit enough human subjects with diverse backgrounds to generate significant statistical power, while critics raise concerns about unreliable data quality, labor exploitation, and unequal power dynamics between researchers and workers. We examine these concerns along three dimensions: methods, fairness, and politics. We find that researchers offer vastly different compensation rates for crowdsourced tasks, and address potential concerns about data validity by using platform-specific tools and user verification methods. Additionally, workers depend upon crowdsourcing platforms for a significant portion of their income, are motivated more by fear of losing access to work than by specific compensation rates, and are frustrated by a lack of transparency and occasional unfair treatment from job requesters. Finally, we discuss critical computing scholars’ proposals to address crowdsourcing’s problems, challenges with implementing these resolutions, and potential avenues for future research.
众包作为研究工具:方法、公平和政治考虑
众包平台是学术研究人员的强大工具。支持者声称,众包有助于研究人员快速、经济地招募足够多的不同背景的人类受试者,以产生显著的统计能力,而批评者则对不可靠的数据质量、劳动力剥削以及研究人员和工人之间不平等的权力动态表示担忧。我们从三个维度来审视这些问题:方法、公平和政治。我们发现,研究人员为众包任务提供了截然不同的补偿率,并通过使用特定平台的工具和用户验证方法解决了对数据有效性的潜在担忧。此外,工人的很大一部分收入依赖众包平台,他们的动机更多地是担心失去工作机会,而不是特定的薪酬水平,他们对缺乏透明度和偶尔受到求职者的不公平待遇感到沮丧。最后,我们讨论了关键计算学者解决众包问题的建议,实施这些解决方案的挑战,以及未来研究的潜在途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Bulletin of Science, Technology and Society
Bulletin of Science, Technology and Society Arts and Humanities-History and Philosophy of Science
CiteScore
2.60
自引率
0.00%
发文量
9
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