Fair prediction with disparate impact: A study of bias in recidivism prediction instruments

24 October 2016

Papers citing "Fair prediction with disparate impact: A study of bias in recidivism prediction instruments"

50 / 866 papers shown

Title
Avoiding Disparity Amplification under Different Worldviews Samuel Yeom Michael Carl Tschantz 151 21 0 26 Aug 2018
The Social Cost of Strategic Classification S. Milli John Miller Anca Dragan Moritz Hardt 114 188 0 25 Aug 2018
An Empirical Study of Rich Subgroup Fairness for Machine Learning Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu FaML 159 211 0 24 Aug 2018
Approximation Trees: Statistical Stability in Model Distillation Yichen Zhou Zhengze Zhou Giles Hooker 183 23 0 22 Aug 2018
Correspondences between Privacy and Nondiscrimination: Why They Should Be Studied Together Anupam Datta S. Sen Michael Carl Tschantz 85 5 0 06 Aug 2018
A Central Limit Theorem for $L_p$ transportation cost with applications to Fairness Assessment in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes 62 2 0 18 Jul 2018
Confidence Intervals for Testing Disparate Impact in Fair Learning Philippe C. Besse E. del Barrio Paula Gordaliza Jean-Michel Loubes CML 80 19 0 17 Jul 2018
Welfare and Distributional Impacts of Fair Classification Lily Hu Yiling Chen FaML 91 24 0 03 Jul 2018
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices Till Speicher Hoda Heidari Nina Grgic-Hlaca Krishna P. Gummadi Adish Singla Adrian Weller Muhammad Bilal Zafar FaML 216 273 0 02 Jul 2018
A Broader View on Bias in Automated Decision-Making: Reflecting on Epistemology and Dynamics Roel Dobbe Sarah Dean T. Gilbert Nitin Kohli 110 41 0 02 Jul 2018
Gradient Reversal Against Discrimination Edward Raff Jared Sylvester 86 41 0 01 Jul 2018
Equalizing Financial Impact in Supervised Learning Govind Ramnarayan FaML 35 1 0 24 Jun 2018
Fairness Under Composition Cynthia Dwork Christina Ilvento FaML 141 128 0 15 Jun 2018
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees L. E. Celis Lingxiao Huang Vijay Keswani Nisheeth K. Vishnoi FaML 324 319 0 15 Jun 2018
What About Applied Fairness? Jared Sylvester Edward Raff FaML 147 11 0 13 Jun 2018
Obtaining fairness using optimal transport theory E. del Barrio Fabrice Gamboa Paula Gordaliza Jean-Michel Loubes FaML 247 189 0 08 Jun 2018
Assessing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour Emilia Gómez Carlos Castillo V. Charisi V. Dahl G. Deco ... Núria Sebastián Xavier Serra Joan Serrà Songül Tolan Karina Vold 75 11 0 07 Jun 2018
POTs: Protective Optimization Technologies B. Kulynych R. Overdorf Carmela Troncoso Seda F. Gürses 172 97 0 07 Jun 2018
Removing Algorithmic Discrimination (With Minimal Individual Error) El-Mahdi El-Mhamdi R. Guerraoui L. Hoang Alexandre Maurer 50 2 0 07 Jun 2018
Causal Interventions for Fairness Matt J. Kusner Chris Russell Joshua R. Loftus Ricardo M. A. Silva FaML 154 15 0 06 Jun 2018
iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making Preethi Lahoti Krishna P. Gummadi Gerhard Weikum FaML 111 176 0 04 Jun 2018
The Externalities of Exploration and How Data Diversity Helps Exploitation Manish Raghavan Aleksandrs Slivkins Jennifer Wortman Vaughan Zhiwei Steven Wu 256 54 0 01 Jun 2018
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification Michael P. Kim Amirata Ghorbani James Zou MLAU 317 352 0 31 May 2018
Why Is My Classifier Discriminatory? Irene Y. Chen Fredrik D. Johansson David Sontag FaML 161 407 0 30 May 2018
Causal Reasoning for Algorithmic Fairness Joshua R. Loftus Chris Russell Matt J. Kusner Ricardo M. A. Silva FaML CML 115 132 0 15 May 2018
Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems S. Kiritchenko Saif M. Mohammad FaML 142 455 0 11 May 2018
Unleashing Linear Optimizers for Group-Fair Learning and Optimization Daniel Alabi Nicole Immorlica Adam Tauman Kalai FedML FaML 83 27 0 11 Apr 2018
Delayed Impact of Fair Machine Learning Lydia T. Liu Sarah Dean Esther Rolf Max Simchowitz Moritz Hardt FaML 222 491 0 12 Mar 2018
Probably Approximately Metric-Fair Learning G. Rothblum G. Yona FaML FedML 107 88 0 08 Mar 2018
Fairness Through Computationally-Bounded Awareness Michael P. Kim Omer Reingold G. Rothblum FaML 153 146 0 08 Mar 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 412 1,131 0 06 Mar 2018
Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction Nina Grgic-Hlaca Elissa M. Redmiles Krishna P. Gummadi Adrian Weller FaML 96 236 0 26 Feb 2018
Path-Specific Counterfactual Fairness Silvia Chiappa Thomas P. S. Gillam CML FaML 190 349 0 22 Feb 2018
Manipulating and Measuring Model Interpretability Forough Poursabzi-Sangdeh D. Goldstein Jake M. Hofman Jennifer Wortman Vaughan Hanna M. Wallach 190 716 0 21 Feb 2018
Online Learning with an Unknown Fairness Metric Stephen Gillen Christopher Jung Michael Kearns Aaron Roth FaML 144 146 0 20 Feb 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 537 703 0 17 Feb 2018
A comparative study of fairness-enhancing interventions in machine learning Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian Sonam Choudhary Evan P. Hamilton Derek Roth FaML 201 663 0 13 Feb 2018
Convex Formulations for Fair Principal Component Analysis Matt Olfat A. Aswani FaML 116 52 0 11 Feb 2018
Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making Michael Veale Max Van Kleek Reuben Binns 113 431 0 03 Feb 2018
Matching Code and Law: Achieving Algorithmic Fairness with Optimal Transport Meike Zehlike P. Hacker Emil Wiedemann 82 19 0 21 Dec 2017
Paradoxes in Fair Computer-Aided Decision Making Andrew Morgan R. Pass FaML 76 9 0 29 Nov 2017
Calibration for the (Computationally-Identifiable) Masses Úrsula Hébert-Johnson Michael P. Kim Omer Reingold G. Rothblum FaML 117 88 0 22 Nov 2017
Does mitigating ML's impact disparity require treatment disparity? Zachary Chase Lipton Alexandra Chouldechova Julian McAuley 103 16 0 19 Nov 2017
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer David Madras T. Pitassi R. Zemel FaML 253 234 0 17 Nov 2017
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu FaML 437 806 0 14 Nov 2017
Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation S. Tan R. Caruana Giles Hooker Yin Lou MLAU 223 191 0 17 Oct 2017
Fair Kernel Learning Adrián Pérez-Suay Valero Laparra Gonzalo Mateo-García Jordi Munoz-Marí L. Gómez-Chova Gustau Camps-Valls FaML 86 86 0 16 Oct 2017
On Fairness and Calibration Geoff Pleiss Manish Raghavan Felix Wu Jon M. Kleinberg Kilian Q. Weinberger FaML 273 905 0 06 Sep 2017
Decoupled classifiers for fair and efficient machine learning Cynthia Dwork Nicole Immorlica Adam Tauman Kalai Max D. M. Leiserson FaML 94 43 0 20 Jul 2017
Calibrated Fairness in Bandits Zehua Wang Goran Radanović Christos Dimitrakakis Debmalya Mandal David C. Parkes FedML FaML 85 92 0 06 Jul 2017