Directly Discriminatory Algorithms

被引:46
作者
Adams-Prassl, Jeremias [1 ]
Binns, Reuben [2 ]
Kelly-Lyth, Aislinn [3 ]
机构
[1] Univ Oxford, Magdalen Coll, Law, Oxford, England
[2] Univ Oxford, Dept Comp Sci, Human Ctr Comp, Oxford, England
[3] Univ Oxford, Bonavero Inst Human Rights, Oxford, England
基金
欧洲研究理事会;
关键词
FAIRNESS;
D O I
10.1111/1468-2230.12759
中图分类号
D9 [法律]; DF [法律];
学科分类号
0301 ;
摘要
Discriminatory bias in algorithmic systems is widely documented. How should the law respond? A broad consensus suggests approaching the issue principally through the lens of indirect discrimination, focusing on algorithmic systems' impact. In this article, we set out to challenge this analysis, arguing that while indirect discrimination law has an important role to play, a narrow em on this regime in the context of machine learning algorithms is both normatively undesirable and legally flawed. We illustrate how certain forms of algorithmic bias in frequently deployed algorithms might constitute direct discrimination, and explore the ramifications-both in practical terms, and the broader challenges automated decision-making systems pose to the conceptual apparatus of anti-discrimination law.
引用
收藏
页码:144 / 175
页数:32
相关论文
共 159 条
[61]  
[Anonymous], 2006, DEFENCE ELIAS
[62]  
[Anonymous], 2016, URSO DEP WORK PENSIO
[63]  
[Anonymous], HILL REVENUE COMMISS
[64]  
[Anonymous], 2000, GLASGOW CITY COUNCIL
[65]  
[Anonymous], GALINA MEISTER SPEEC
[66]  
[Anonymous], 1989, R BIRMINGHAM CITY CO
[67]  
[Anonymous], 2021, WLR
[68]  
[Anonymous], JENKINS KINGSGATE CL
[69]  
[Anonymous], 2014, INDIGO DESIGN BUILD
[70]  
[Anonymous], 2014, WLR