Berkman Klein Center for Internet and Society: Audio Fishbowl

Why Fairness Cannot Be Automated


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Fairness and discrimination in algorithmic systems are globally recognized as topics of critical importance. To date, the majority of work in this area starts from an American regulatory perspective defined by the notions of ‘disparate treatment’ and ‘disparate impact.’ But European legal notions of discrimination are not equivalent.
In this talk, Sandra Wachter, Visiting Professor at Harvard Law School and Associate Professor and Senior Research Fellow in Law and Ethics of AI, Big Data, robotics and Internet Regulation at the Oxford Internet Institute (OII) at the University of Oxford, examines EU law and jurisprudence of the European Court of Justice concerning non-discrimination and identifies a critical incompatibility between European notions of discrimination and existing work on algorithmic and automated fairness.
Wachter discusses the evidential requirements for bringing a claim under EU non-discrimination law and propose a statistical test as a baseline to identify and assess potential cases of algorithmic discrimination in Europe.
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Berkman Klein Center for Internet and Society: Audio FishbowlBy Berkman Klein Center for Internet & Society at Harvard University

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