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Fairness and machine learning Fairness and machine learning Limitations and Opportunities Solon Barocas, Moritz Hardt, Arvind Narayanan CONTENTS Preface Acknowledgments 1 Introduction PDF 2 When is automated decision making legitimate? PDF We explore what makes automated decision making a matter of normative concern, situated in bureaucratic decision making and its mechanical application of formalized rules. 3 Classification PDF We introduce formal non-discrimination criteria in a decision-theoretic setting, establish their relationships, and illustrate their limitations. 4 Relative notions of fairness PDF We explore the normative underpinnings of objections to systematic differences in the treatment of different groups and inequalities in the outcomes experienced by these groups. 5 Causality PDF We dive into the technical repertoire of causality and how it helps articulate and address shortcomings of the classification paradigm, while ...
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