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Decision makers increasingly rely on algorithmic risk scores to determine access to binary treatments including bail, loans, and medical interventions.
A possibility in algorithmic fairness: Calibrated scores for fair classifications, 2020
Claire Lazar Reich and Suhas Vijaykumar · 2002
Earlier work this paper cites.
Model selection in nonparametric regression
Marten Wegkamp · 2003
Earlier work this paper cites.
Information, Physics, and Computation
Marc Mezard and Andrea Montanari · 2009
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Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel · 2012
Earlier work this paper cites.
Survey of income and program participation, 2014
U.S. Census Bureau · 2014
Earlier work this paper cites.
Bias in Criminal Risk Scores Is Mathematically Inevitable, Researchers Say
Julia Angwin and Jeff Larson · 2016
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Machine Bias
Julia Angwin and Jeff Larson · 2016
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Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments
Alexandra Chouldechova · 2016
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A computer program used for bail and sentencing decisions was labeled biased against blacks. it’s actually not that clear
Avi Feller, Emma Pierson, Sam Corbett-Davies, and Sharad Goel · 2016
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Equality of Opportunity in Supervised Learning
Moritz Hardt, Eric Price, Eric Price, and Nati Srebro · 2016
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Algorithmic decision making and the cost of fairness
Sam Corbett-Davies, Emma Pierson, Avi Feller, Sharad Goel, and Aziz Huq · 2017
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Inherent trade-offs in the fair determination of risk scores
Jon M. Kleinberg, Sendhil Mullainathan, and Manish Raghavan · 2017
Cited alongside, same era.
Data and analysis for “Machine bias”
Jeff Larson · 2017
Cited alongside, same era.
On Fairness and Calibration
Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger · 2017
Cited alongside, same era.
Decoupled classifiers for group-fair and efficient machine learning
Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, and Max Leiserson · 2018
Later among the works it cites.
Algorithmic Fairness
Jon Kleinberg, Jens Ludwig, Sendhil Mullainathan, and Ashesh Rambachan · 2018
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Tracking and improving information in the service of fairness
Sumegha Garg, Michael P. Kim, and Omer Reingold · 2019
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Simplicity creates inequity: Implications for fairness, stereotypes, and interpretability
Jon Kleinberg and Sendhil Mullainathan · 2019
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Computational optimal transport
Gabriel Peyré, Marco Cuturi, et al · 2019
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Performative prediction
Juan Perdomo, Tijana Zrnic, Celestine Mendler-Dünner, and Moritz Hardt · 2020
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Fairness in criminal justice risk assessments: The state of the art
Richard Berk, Hoda Heidari, Shahin Jabbari, Michael Kearns, and Aaron Roth · 2018
Cited alongside, same era.
The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning
Sam Corbett-Davies and Sharad Goel · 2018
Cited alongside, same era.
How We Analyzed the COMPAS Recidivism Algorithm
Jeff Larson, Surya Mattu, Lauren Kirchner, and Julia Angwin
Cited in the paper.
Causal strategic linear regression
Yonadav Shavit, Benjamin Edelman, and Brian Axelrod · 2020
Closest in time.