Tuning EU Equality Law to Algorithmic Discrimination: Three Pathways to Resilience
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Tuning EU Equality Law to Algorithmic Discrimination: Three Pathways to Resilience. / Xenidis, Raphaële.
I: Maastricht Journal of European and Comparative Law, Bind 27, Nr. 6, 04.01.2021, s. 736–758.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Tuning EU Equality Law to Algorithmic Discrimination: Three Pathways to Resilience
AU - Xenidis, Raphaële
PY - 2021/1/4
Y1 - 2021/1/4
N2 - Algorithmic discrimination poses an increased risk to the legal principle of equality. Scholarly accounts of this challenge are emerging in the context of EU equality law, but the question of the resilience of the legal framework has not yet been addressed in depth. Exploring three central incompatibilities between the conceptual map of EU equality law and algorithmic discrimination, this article investigates how purposively revisiting selected conceptual and doctrinal tenets of EU non-discrimination law offers pathways towards enhancing its effectiveness and resilience. First, I argue that predictive analytics are likely to give rise to intersectional forms of discrimination, which challenge the unidimensional understanding of discrimination prevalent in EU law. Second, I show how proxy discrimination in the context of machine learning questions the grammar of EU non-discrimination law. Finally, I address the risk that new patterns of systemic discrimination emerge in the algorithmic society. Throughout the article, I show that looking at the margins of the conceptual and doctrinal map of EU equality law offers several pathways to tackling algorithmic discrimination. This exercise is particularly important with a view to securing a technology-neutral legal framework robust enough to provide an effective remedy to algorithmic threats to fundamental rights.
AB - Algorithmic discrimination poses an increased risk to the legal principle of equality. Scholarly accounts of this challenge are emerging in the context of EU equality law, but the question of the resilience of the legal framework has not yet been addressed in depth. Exploring three central incompatibilities between the conceptual map of EU equality law and algorithmic discrimination, this article investigates how purposively revisiting selected conceptual and doctrinal tenets of EU non-discrimination law offers pathways towards enhancing its effectiveness and resilience. First, I argue that predictive analytics are likely to give rise to intersectional forms of discrimination, which challenge the unidimensional understanding of discrimination prevalent in EU law. Second, I show how proxy discrimination in the context of machine learning questions the grammar of EU non-discrimination law. Finally, I address the risk that new patterns of systemic discrimination emerge in the algorithmic society. Throughout the article, I show that looking at the margins of the conceptual and doctrinal map of EU equality law offers several pathways to tackling algorithmic discrimination. This exercise is particularly important with a view to securing a technology-neutral legal framework robust enough to provide an effective remedy to algorithmic threats to fundamental rights.
KW - Faculty of Law
KW - algorithmic discrimination
KW - non-discrimination law
KW - equality
KW - European Union
KW - algorithms
KW - machine Learning
KW - artificial intelligence
KW - profiling
KW - predictive analytics
KW - legal resilience
U2 - 10.1177/1023263X20982173
DO - 10.1177/1023263X20982173
M3 - Journal article
VL - 27
SP - 736
EP - 758
JO - Maastricht Journal of European and Comparative Law
JF - Maastricht Journal of European and Comparative Law
SN - 1023-263X
IS - 6
ER -
ID: 252521830