The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending Recommendation
The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending Recommendation
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公平的多面性：探索多利益相关方小额贷款建议的制度逻辑
DOI：
10.1145/3593013.3594106
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Voida, Amy
中科院分区：
文献类型：
--
作者：
Smith, Jessie J.;Buhayh, Anas;Kathait, Anushka;Ragothaman, Pradeep;Mattei, Nicholas;Burke, Robin;Voida, Amy
推荐系统有各种各样的利益相关者。在这种制度中应用公平概念需要注意利益攸关方复杂和往往相互冲突的需求。由于公平是社会构建的，因此在社会科学和机器学习文献中有许多定义。尽管如此，机器学习研究人员很少在密切考虑其社会背景的情况下开发他们的指标。更常见的情况是，采用标准定义，并假定这些定义适用于不同的背景和利益攸关方。我们的研究从推荐背景开始，然后试图了解相关利益相关者的公平性考虑的广度。在本文中，我们报告了一个半结构化的访谈研究的结果与23名员工谁为Kiva小额贷款平台工作。我们描述了他们在自己的工作中制定并努力实现小额贷款建议公平性的许多不同方式，揭示了这些不同的公平性法规相互之间的紧张关系，并确定了利益相关者如何区分优先级。最后，我们反思这项研究的影响，为未来的研究和多利益相关者推荐系统的设计。
Recommender systems have a variety of stakeholders. Applying concepts of fairness in such systems requires attention to stakeholders’ complex and often-conflicting needs. Since fairness is socially constructed, there are numerous definitions, both in the social science and machine learning literatures. Still, it is rare for machine learning researchers to develop their metrics in close consideration of their social context. More often, standard definitions are adopted and assumed to be applicable across contexts and stakeholders. Our research starts with a recommendation context and then seeks to understand the breadth of the fairness considerations of associated stakeholders. In this paper, we report on the results of a semi-structured interview study with 23 employees who work for the Kiva microlending platform. We characterize the many different ways in which they enact and strive toward fairness for microlending recommendations in their own work, uncover the ways in which these different enactments of fairness are in tension with each other, and identify how stakeholders are differentially prioritized. Finally, we reflect on the implications of this study for future research and for the design of multistakeholder recommender systems.
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DOI：
10.1145/3269206.3271795
发表时间：
2018-10
期刊：
Proceedings of the 27th ACM International Conference on Information and Knowledge Management
影响因子：
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作者：
Ziwei Zhu;Xia Hu;James Caverlee
通讯作者：
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DOI：
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发表时间：
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期刊：
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影响因子：
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DOI：
10.1145/3450613.3456835
发表时间：
2021-03
期刊：
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影响因子：
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作者：
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通讯作者：
Nasim Sonboli;Jessie J. Smith;Florencia Cabral Berenfus;R. Burke;Casey Fiesler
DOI：
10.48550/arxiv.2209.04043
发表时间：
2022
期刊：
ArXiv
影响因子：
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作者：
Paresha Farastu;Nicholas Mattei;R. Burke
通讯作者：
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“获胜者是……”：多组公平意识推荐的动态抽签
DOI：
--
发表时间：
2020
期刊：
arXiv.org
影响因子：
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作者：
Nasim Sonboli;R. Burke;Nicholas Mattei;Farzad Eskandanian;Tian Gao
通讯作者：
Tian Gao