Teaching fairness to articial intelligence : existing and novel strategies against algorithmic discrimination under EU law / Philipp Hacker 

Public ISBD Titre : Teaching fairness to articial intelligence : existing and novel strategies against algorithmic discrimination under EU law Type de document : document électronique Auteurs : Philipp Hacker, Auteur Editeur : The Hague : Kluwer Law International Année de publication : 2018 Importance : 43 p ISBN/ISSN/EAN : 0165-0750 Langues : Anglais Catégories : DROIT : Droit européen DROIT : Droit européen : Internet Tags : discrimination  plateforme  protection des données  droit  Europe Résumé : "Empirical evidence is mounting that artificial intelligence applications threaten to discriminate against legally protected groups. This raises intricate questions for EU law. The existing categories of EU anti-discrimination law do not provide an easy fit for algorithmic decision making. Furthermore, victims won’t be able to prove their case without access to the data and the algorithmic models. Drawing on a growing computer science literature on algorithmic fairness, this article suggests an integrated vision of anti-discrimination and data protection law to enforce fairness in the digital age. It shows how the concepts of anti-discrimination law may be combined with algorithmic audits and data protection impact assessments in an effort to unlock the algorithmic black box." Source : https://www.kluwerlawonline.com/abstract.php?area=Journals&id=COLA2018095 (consulté le 7/1/2019) En ligne : https://www.kluwerlawonline.com/abstract.php?area=Journals&id=COLA2018095 Teaching fairness to articial intelligence : existing and novel strategies against algorithmic discrimination under EU law [document électronique] / Philipp Hacker, Auteur . - The Hague (P.O. Box 85889, 2508 CN) : Kluwer Law International, 2018 . - 43 p. ISSN : 0165-0750 Langues : Anglais Catégories : DROIT : Droit européen DROIT : Droit européen : Internet Tags : discrimination  plateforme  protection des données  droit  Europe Résumé : "Empirical evidence is mounting that artificial intelligence applications threaten to discriminate against legally protected groups. This raises intricate questions for EU law. The existing categories of EU anti-discrimination law do not provide an easy fit for algorithmic decision making. Furthermore, victims won’t be able to prove their case without access to the data and the algorithmic models. Drawing on a growing computer science literature on algorithmic fairness, this article suggests an integrated vision of anti-discrimination and data protection law to enforce fairness in the digital age. It shows how the concepts of anti-discrimination law may be combined with algorithmic audits and data protection impact assessments in an effort to unlock the algorithmic black box." Source : https://www.kluwerlawonline.com/abstract.php?area=Journals&id=COLA2018095 (consulté le 7/1/2019) En ligne : https://www.kluwerlawonline.com/abstract.php?area=Journals&id=COLA2018095

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