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6 May 2024: Prior work in economics, law, and political science dis-tinguishes between direct and indirect discrimination, sug-gesting that the “wrong” of direct discrimination (which weidentify with violating process fairness) should be ... In Univer-sity of

6 May 2024: physics (Jordan et al., 1998) and economics(Galichon, 2016), and are increasingly used in machinelearning (Arjovsky et al., 2017; Gulrajani et al., 2017;Peyré and Cuturi, 2018).

6 May 2024: 3. Prior literature in social, economic, legal, and political sciences distinguishing between directdiscrimination and indirect discrimination makes similar observations as we do in this paper.

6 May 2024: 1. IntroductionLearning interpretable data representations is becomingever more important as machine learning models grow insize and complexity, and as applications reach critical so-cial, economic and public health domains.

6 May 2024: Our core idea is to use existing inequalityindices from economics to measure how unequally the outcomes ofan algorithm benefit different individuals or groups in a population.Our work offers a justified ... In this paper, we propose to quantify

6 May 2024: In UAI, 2009. P. Milgrom. The envelope theorems. Department of Economics, Standford University, Mimeo, 1999.

6 May 2024: In this paper, we draw inspiration from the fair-division and envy-freeness literature in economics and game theory and proposepreference-based notions of fairness—given the choice between various sets ... In this work, we introduce, formalize and

6 May 2024: cave functions. They have attracted attention in combinatorics (Lovász, 1983), economics (Topkis,.

6 May 2024: Naturally incorporate spatial information. • Applications from economics to machine learning.

6 May 2024: Working Draft. 1. Accountability of AI Under the Law: The Role of Explanation. Finale Doshi-Velez, Mason Kortz, Ryan Budish, Chris Bavitz, Sam Gershman, David O’Brien, Kate Scott, Stuart Shieber, James Waldo, David Weinberger, Adrian Weller,.