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DTSTAMP:20260407T134903Z
SUMMARY:Why Fairness Cannot Be Automated
DESCRIPTION:Fairness and discrimination in algorithmic systems are globally
  recognized as topics of critical importance. To date\, the majority of wo
 rk in this area starts from an American regulatory perspective defined by 
 the notions of ‘disparate treatment’ and ‘disparate impact.’ But E
 uropean legal notions of discrimination are not equivalent.&nbsp\;In this 
 talk\, Sandra Wachter\, Visiting Professor at Harvard Law School and Assoc
 iate Professor and Senior Research Fellow in Law and Ethics of AI\, Big Da
 ta\, robotics and Internet Regulation at the Oxford Internet Institute (OI
 I) at the University of Oxford\, examines EU law and jurisprudence of the 
 European Court of Justice concerning non-discrimination and identifies&nbs
 p\;a critical incompatibility between European notions of discrimination a
 nd existing work on algorithmic and automated fairness.&nbsp\;Wachter disc
 usses&nbsp\;the evidential requirements for bringing a claim under EU non-
 discrimination law and propose a statistical test as a baseline to identif
 y and assess potential cases of algorithmic discrimination in Europe.
DTSTART;TZID=Europe/Berlin:20200414T120000
DTEND;TZID=Europe/Berlin:20200414T130000
LOCATION:23 Everett Street \, Cambridge (United States of America) 
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DESCRIPTION:Why Fairness Cannot Be Automated
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