Building and Auditing Fair Algorithms: A Case Study in Candidate Screening
Building and Auditing Fair Algorithms: A Case Study in Candidate Screening
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构建和审核公平算法：候选人筛选案例研究
DOI：
10.1145/3442188.3445928
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Frida Polli
中科院分区：
文献类型：
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作者：
Christo Wilson;A. Ghosh;Shan Jiang;A. Mislove;Lewis Baker;Janelle Szary;Kelly Trindel;Frida Polli
学者、活动家和监管机构越来越多地敦促公司开发和部署公平和不偏不倚的社会技术体系。然而，实现这一目标是复杂的：开发人员必须(1)在给定的上下文中深入参与“公平”的社会和法律方面，(2)开发具体化这些价值观的软件，(3)接受独立的算法审计，以确保他们的算法的技术正确性和社会责任感。到目前为止，几乎没有公司透明地采取了这三个步骤。在这篇文章中，我们通过对PYMETRICS的案例研究，概述了算法审计的框架。PYMETRICS是一家利用机器学习向客户推荐求职者的初创公司。我们讨论了在道德、法规和客户需求的约束下，PYMETRICS如何处理公平性问题，以及PYMETRICS的软件如何实现不利影响测试。我们还介绍了对PYMETRICS的候选人筛选工具进行独立审计的结果。最后，我们就如何构建实用、独立和建设性的审计结构提出了建议，以便公司有更好的动机参与第三方审计，监督小组可以更好地准备对公司进行调查。
Academics, activists, and regulators are increasingly urging companies to develop and deploy sociotechnical systems that are fair and unbiased. Achieving this goal, however, is complex: the developer must (1) deeply engage with social and legal facets of "fairness" in a given context, (2) develop software that concretizes these values, and (3) undergo an independent algorithm audit to ensure technical correctness and social accountability of their algorithms. To date, there are few examples of companies that have transparently undertaken all three steps. In this paper we outline a framework for algorithmic auditing by way of a case-study of pymetrics, a startup that uses machine learning to recommend job candidates to their clients. We discuss how pymetrics approaches the question of fairness given the constraints of ethical, regulatory, and client demands, and how pymetrics' software implements adverse impact testing. We also present the results of an independent audit of pymetrics' candidate screening tool. We conclude with recommendations on how to structure audits to be practical, independent, and constructive, so that companies have better incentive to participate in third party audits, and that watchdog groups can be better prepared to investigate companies.
自动化作为反偏见干预的悖论
DOI：
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发表时间：
2020
期刊：
Cardozo law review
影响因子：
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作者：
Ajunwa, Ifeoma
通讯作者：
Ajunwa, Ifeoma
预测警务中失控的反馈循环
DOI：
--
发表时间：
2018
期刊：
and Transparency
影响因子：
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作者：
Ensign, Danielle;Friedler, Sorelle A.;Neville, Scott;Scheidegger, Carlos;Venkatasubramanian, Suresh
通讯作者：
Venkatasubramanian, Suresh
审计新闻策展系统：检查 Apple News 中算法和编辑逻辑的案例研究
DOI：
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发表时间：
2020
期刊：
Proceedings of the International AAAI Conference on Weblogs and Social Media
影响因子：
--
作者：
Jack Bandy, Nicholas Diakopoulos
通讯作者：
Jack Bandy, Nicholas Diakopoulos