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EU non-discrimination law in the era of artificial intelligence : mapping the challenges of algorithmic discrimination
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Ulf BERNITZ, Xavier GROUSSOT, Jaan PAJU and Sybe A. DE VRIES (eds), General principles of EU law and the EU digital order, Alphen aan den Rijn : Kluwer Law International, 2020, pp. 151-182
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XENIDIS, Raphaële, SENDEN, Linda, EU non-discrimination law in the era of artificial intelligence : mapping the challenges of algorithmic discrimination, in Ulf BERNITZ, Xavier GROUSSOT, Jaan PAJU and Sybe A. DE VRIES (eds), General principles of EU law and the EU digital order, Alphen aan den Rijn : Kluwer Law International, 2020, pp. 151-182 - https://hdl.handle.net/1814/65845
Abstract
While most studies on the topic of AI, algorithms and bias have been conducted from the point of view of ‘fairness’ in the field of information technologies and computer science, this chapter explores the question of algorithmic discrimination – a category that does not neatly overlap with algorithmic bias – from the specific perspective of non-discrimination law. In particular and by contrast to the majority of current research on the question of algorithms and discrimination, which focuses on the United States context, this chapter takes EU non-discrimination law as its object of enquiry. We pose the question of the resilience of the general principle of non-discrimination, that is, the capacity for EU equality law to respond effectively to the specific challenges posed by algorithmic discrimination. Because EU law represents an overarching framework and sets minimum safeguards for the protection against discrimination at national level in EU Member States, it is important to test out the protection against the risks posed by the pervasive and increasing use of AI techniques in everyday life applications which this framework allows for. This chapter therefore maps the challenges arising from artificial intelligence for equality and non-discrimination, which are both a general principle and a fundamental right in EU law. First, we identify the specific risks of discrimination that AI-based decision-making, and in particular machine-learning algorithms, pose. Second, we review how EU non-discrimination law can capture algorithmic discrimination in terms of its substantive scope. Third, we conduct this review from a conceptual perspective, mapping the friction points that emerge from the perspective of the EU concepts of direct and indirect discrimination, as developed by the Court of Justice of the European Union (CJEU). In the final step, we identify the core challenges algorithmic discrimination poses at the enforcement level and propose potential ways forward.