Crowdsourcing platforms such as Amazon Mechanical Turk (MTurk) are popular and widely used in both academic and non-academic realms, but privacy threats and challenges in crowdsourcing have not been extensively reviewed. To help push the field forward in important new directions, this paper first reviews the privacy threats in different types of crowdsourcing based on Solove’s taxonomy of privacy and Brabham’s typology of crowdsourcing. Then, the paper explores the privacy challenges associated with the characteristics of crowdsourcing task, platform, requesters, and crowd workers. These privacy challenges are discussed and categorized into both theoretical and practical challenges. Based on the review and discussion, this paper proposes a set of strategies to better understand and address many of the privacy threats and challenges in crowdsourcing. Finally, the paper concludes by suggesting research implications for the future work.

中文翻译：

---

众包中的隐私：威胁与挑战的回顾

诸如Amazon Mechanical Turk（MTurk）之类的众包平台在学术领域和非学术领域都非常流行并得到广泛使用，但是众包中的隐私威胁和挑战尚未得到广泛的审查。为了帮助在重要的新方向上推动这一领域的发展，本文首先基于索洛夫的隐私分类法和布拉汉姆的众包类型，回顾了不同类型众包中的隐私威胁。然后，本文探讨了与众包任务，平台，请求者和人群工作者的特征相关的隐私挑战。讨论了这些隐私挑战并将其分为理论挑战和实践挑战。根据评论和讨论，本文提出了一套策略，以更好地理解和应对众包中的许多隐私威胁和挑战。最后，本文通过建议对未来工作的研究意义进行总结。