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Black-box risk scoring models permeate our lives, yet are typically proprietary or opaque.
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Machine Bias: There’s software used across the country to predict future criminals. And it’s biased against blacks
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016b · 2017
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Algorithmic decision making and the cost of fairness. In KDD
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Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems. In IEEE Symposium on Security and Privacy
A. Datta, S. Sen, and Y. Zick. 2016 · 2016
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COMPAS risk scales: Demonstrating accuracy equity and predictive parity
William Dieterich, Christina Mendoza, and Tim Brennan. 2016 · 2016
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Precinct or prejudice? Understanding racial disparities in New York City’s stop-and-frisk policy
Sharad Goel, Justin M. Rao, and Ravi Shroff. 2016 · 2016
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Classification methods applied to credit scoring: Systematic review and overall comparison
Francisco Louzada, Anderson Ara, and Guilherme B Fernandes. 2016 · 2016
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Quantifying uncertainty in random forests via confidence intervals and hypothesis tests
Lucas Mentch and Giles Hooker. 2016 · 2016
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External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges
Richard D Riley, Joie Ensor, Kym IE Snell, Thomas PA Debray, Doug G Altman, Karel GM Moons, and Gary S Collins. 2016 · 2016
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How we analyzed the compas recidivism algorithm
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016a · 2017
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Finale Doshi-Velez and Been Kim. 2017 · 2017
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Inherent trade-offs in the fair determination of risk scores. In Innovations in Theoretical Computer Science
Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan. 2017 · 2017
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FairTest: Discovering Unwarranted Associations in Data-Driven Applications. In IEEE European Symposium on Security and Privacy
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Transparent Model Distillation
Sarah Tan, Rich Caruana, Giles Hooker, and Albert Gordo. 2018 · 2018
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Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR
Sandra Wachter, Brent Mittelstadt, and Chris Russell. 2018 · 2018
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On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning. In International Symposium on Information Theory
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