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Fairness in machine learning has predominantly been studied in static classification settings without concern for how decisions change the underlying population over time.
Effects of affirmative action in medical schools
Stephen N. Keith, Robert M. Bell, August G. Swanson, and Albert P. Williams · 1985
Earlier work this paper cites.
An economic argument for affirmative action
Dean P Foster and Rakesh V Vohra · 1992
Earlier work this paper cites.
Best Practices or Best Guesses? Assessing the Efficacy of Corporate Affirmative Action and Diversity Policies
Alexandra Kalev, Frank Dobbin, and Erin Kelly · 2006
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The Color of Credit: Mortgage Discrimination, Research Methodology, and Fair-Lending Enforcement
Stephen Ross and John Yinger · 2006
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Report to the congress on credit scoring and its effects on the availability and affordability of credit, 2007
US Federal Reserve · 2007
Earlier work this paper cites.
Building classifiers with independency constraints
Toon Calders, Faisal Kamiran, and Mykola Pechenizkiy · 2009
Earlier work this paper cites.
Big data’s disparate impact
Solon Barocas and Andrew D. Selbst · 2016
Earlier work this paper cites.
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova · 2016
Cited alongside, same era.
Big data: A report on algorithmic systems, opportunity, and civil rights
Executive Office of the President · 2016
Cited alongside, same era.
Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nati Srebro · 2016
Cited alongside, same era.
Fairness in learning: Classic and contextual bandits
Matthew Joseph, Michael Kearns, Jamie H Morgenstern, and Aaron Roth · 2016
Cited alongside, same era.
Runaway feedback loops in predictive policing
Danielle Ensign, Sorelle A Friedler, Scott Neville, Carlos Scheidegger, and Suresh Venkatasubramanian · 2017
Cited alongside, same era.
Predictably unequal? the effects of machine learning on credit markets
Inherent trade-offs in the fair determination of risk scores
Jon M. Kleinberg, Sendhil Mullainathan, and Manish Raghavan · 2017
Later among the works it cites.
Counterfactual fairness
Matt J. Kusner, Joshua R. Loftus, Chris Russell, and Ricardo Silva · 2017
Later among the works it cites.
Razieh Nabi and Ilya Shpitser · 2017
Later among the works it cites.
On fairness and calibration
Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger · 2017
Later among the works it cites.
Fairness Constraints: Mechanisms for Fair Classification
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rogriguez, and Krishna P. Gummadi · 2017
Later among the works it cites.
A short-term intervention for long-term fairness in the labor market
Lily Hu and Yiling Chen · 2018
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Andreas Fuster, Paul Goldsmith-Pinkham, Tarun Ramadorai, and Ansgar Walther · 2017
Cited alongside, same era.
Avoiding discrimination through causal reasoning
Niki Kilbertus, Mateo Rojas-Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, and Bernhard Schölkopf · 2017
Cited alongside, same era.
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