工作中的算法歧视

IF 1.1 Q2 LAW European Labour Law Journal Pub Date : 2023-04-02 DOI:10.1177/20319525231167300
Aislinn Kelly-Lyth
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引用次数: 0

摘要

算法歧视的可能性现在已经得到了充分的证明,算法管理工具也不例外。学者们很快就指出了平等法框架中的漏洞,但现有的欧洲法律相当健全。在差距确实存在的地方,它们在很大程度上早于算法决策。仔细的司法推理可以解决看似新颖的法律问题;政策制定者应该加强欧洲平等法,而不是对其进行改革。本文解开了关于禁止直接和间接歧视对算法管理的应用的一些最棘手的问题,从法律应该如何处理算法比人类决策者“更准确”或“更少偏见”的论点,到就业背景下的责任归属。通过确定司法解决的可能途径,本文论证了现有法律义务的适应性。还审查了在残疾背景下提供合理便利的责任,并探讨了将顶层调整和个性化调整相结合的选择。文章最后谈到了可执行性。算法歧视产生了一个令人担忧的悖论:一方面,自动化以前的人类决策过程可以使歧视标准更可追溯,结果更可量化。另一方面,算法决策过程很少是透明的,学者们一致认为算法不透明是诉讼和执法行动的主要障碍。探索提高透明度的司法和立法途径。
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Algorithmic discrimination at work
The potential for algorithms to discriminate is now well-documented, and algorithmic management tools are no exception. Scholars have been quick to point to gaps in the equality law framework, but existing European law is remarkably robust. Where gaps do exist, they largely predate algorithmic decision-making. Careful judicial reasoning can resolve what appear to be novel legal issues; and policymakers should seek to reinforce European equality law, rather than reform it. This article disentangles some of the knottiest questions on the application of the prohibition on direct and indirect discrimination to algorithmic management, from how the law should deal with arguments that algorithms are ‘more accurate’ or ‘less biased’ than human decision-makers, to the attribution of liability in the employment context. By identifying possible routes for judicial resolution, the article demonstrates the adaptable nature of existing legal obligations. The duty to make reasonable accommodations in the disability context is also examined, and options for combining top-level and individualised adjustments are explored. The article concludes by turning to enforceability. Algorithmic discrimination gives rise to a concerning paradox: on the one hand, automating previously human decision-making processes can render discriminatory criteria more traceable and outcomes more quantifiable. On the other hand, algorithmic decision-making processes are rarely transparent, and scholars consistently point to algorithmic opacity as the key barrier to litigation and enforcement action. Judicial and legislative routes to greater transparency are explored.
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来源期刊
CiteScore
1.60
自引率
28.60%
发文量
29
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