"This book offers a critical view on the current practice of machine learning, as well as proposed technical fixes for achieving fairness in automated decisionmaking"--
Inhaltsverzeichnis
Preface ix
Online Materials xiv
Acknowledgments xv
1 Introduction 1
2 When Is Automated Decision Making Legitimate? 25
3 Classification 49
4 Relative Notions of Fairness 83
5 Causality 113
6 Understanding United States Antidiscrimination Law 151
7 Testing Discrimination in Practice 185
8 A Broader View of Discrimination 221
9 Datasets 251
References 285
Index 311
