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 / 858 papers shown

Title
Individual Fairness for $k$ -Clustering S. Mahabadi A. Vakilian FaML 111 85 0 17 Feb 2020
Convex Fairness Constrained Model Using Causal Effect Estimators Hikaru Ogura Akiko Takeda 24 2 0 16 Feb 2020
Trustworthy AI Jeannette M. Wing 64 220 0 14 Feb 2020
CheXclusion: Fairness gaps in deep chest X-ray classifiers Laleh Seyyed-Kalantari Guanxiong Liu Matthew B. A. McDermott Irene Y. Chen Marzyeh Ghassemi OOD 108 295 0 14 Feb 2020
Metric-Free Individual Fairness in Online Learning Yahav Bechavod Christopher Jung Zhiwei Steven Wu FaML 99 50 0 13 Feb 2020
Solution manifold and Its Statistical Applications Swee Hong Chan 99 7 0 13 Feb 2020
To Split or Not to Split: The Impact of Disparate Treatment in Classification Hao Wang Hsiang Hsu Mario Díaz Flavio du Pin Calmon 115 23 0 12 Feb 2020
Joint Optimization of AI Fairness and Utility: A Human-Centered Approach Yunfeng Zhang Rachel K. E. Bellamy Kush R. Varshney 68 38 0 05 Feb 2020
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism Keri Mallari K. Quinn Paul Johns Sarah Tan Divya Ramesh Ece Kamar FaML 60 30 0 04 Feb 2020
Case Study: Predictive Fairness to Reduce Misdemeanor Recidivism Through Social Service Interventions Kit T. Rodolfa E. Salomon Lauren Haynes Iván Higuera Mendieta Jamie L Larson Rayid Ghani 47 47 0 24 Jan 2020
Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack Bo Zhang Ruotong Yu Haipei Sun Yanying Li Jun Xu Wendy Hui Wang AAML 59 13 0 24 Jan 2020
Algorithmic Fairness Dana Pessach E. Shmueli FaML 102 395 0 21 Jan 2020
Algorithmic Fairness from a Non-ideal Perspective S. Fazelpour Zachary Chase Lipton FaML 66 103 0 08 Jan 2020
On Consequentialism and Fairness Dallas Card Noah A. Smith FaML 68 11 0 02 Jan 2020
Leveraging Semi-Supervised Learning for Fairness using Neural Networks Vahid Noroozi S. Bahaadini Samira Sheikhi Nooshin Mojab Philip S. Yu 129 7 0 31 Dec 2019
Teaching Responsible Data Science: Charting New Pedagogical Territory Julia Stoyanovich Armanda Lewis 49 39 0 23 Dec 2019
Learning from Discriminatory Training Data Przemyslaw A. Grabowicz Nicholas Perello Kenta Takatsu FaML 87 1 0 17 Dec 2019
Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics Debjani Saha Candice Schumann Duncan C. McElfresh John P. Dickerson Michelle L. Mazurek Michael Carl Tschantz FaML 65 17 0 17 Dec 2019
On the Apparent Conflict Between Individual and Group Fairness Reuben Binns FaML 95 316 0 14 Dec 2019
Measurement and Fairness Abigail Z. Jacobs Hanna M. Wallach 90 403 0 11 Dec 2019
Value-laden Disciplinary Shifts in Machine Learning Ravit Dotan S. Milli AILaw 84 48 0 03 Dec 2019
Automated Dependence Plots David I. Inouye Liu Leqi Joon Sik Kim Bryon Aragam Pradeep Ravikumar 64 1 0 02 Dec 2019
Recovering from Biased Data: Can Fairness Constraints Improve Accuracy? Avrim Blum Kevin Stangl FaML 61 87 0 02 Dec 2019
FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions Sebastian Schelter Yuxuan He Jatin Khilnani Julia Stoyanovich 50 61 0 28 Nov 2019
Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty through Sociotechnical Commitments Roel Dobbe T. Gilbert Yonatan Dov Mintz 59 18 0 20 Nov 2019
Fair Data Adaptation with Quantile Preservation Drago Plečko N. Meinshausen 69 30 0 15 Nov 2019
What Do Compressed Deep Neural Networks Forget? Sara Hooker Aaron Courville Gregory Clark Yann N. Dauphin Andrea Frome 118 185 0 13 Nov 2019
Kernel Dependence Regularizers and Gaussian Processes with Applications to Algorithmic Fairness Zhu Li Adrián Pérez-Suay Gustau Camps-Valls Dino Sejdinovic FaML 104 22 0 11 Nov 2019
A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness Mohammad Yaghini A. Krause Hoda Heidari FaML 52 22 0 08 Nov 2019
Learning Fair and Interpretable Representations via Linear Orthogonalization Yuzi He Keith Burghardt Kristina Lerman FaML 23 4 0 28 Oct 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 182 6,380 0 22 Oct 2019
Optimization Hierarchy for Fair Statistical Decision Problems A. Aswani Matt Olfat 58 3 0 18 Oct 2019
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing Sanghamitra Dutta Dennis L. Wei Hazar Yueksel Pin-Yu Chen Sijia Liu Kush R. Varshney FaML 67 11 0 17 Oct 2019
Conditional Learning of Fair Representations Han Zhao Amanda Coston T. Adel Geoffrey J. Gordon FaML 87 109 0 16 Oct 2019
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability Christopher Frye C. Rowat Ilya Feige 105 183 0 14 Oct 2019
Keeping Designers in the Loop: Communicating Inherent Algorithmic Trade-offs Across Multiple Objectives Bowen Yu Ye Yuan Loren G. Terveen Zhiwei Steven Wu Jodi Forlizzi Haiyi Zhu 75 2 0 07 Oct 2019
Group-based Fair Learning Leads to Counter-intuitive Predictions Ofir Nachum Heinrich Jiang FaML 34 2 0 04 Oct 2019
Generating Fair Universal Representations using Adversarial Models Peter Kairouz Jiachun Liao Chong Huang Maunil R. Vyas Monica Welfert Lalitha Sankar 64 17 0 27 Sep 2019
This Thing Called Fairness: Disciplinary Confusion Realizing a Value in Technology D. Mulligan Joshua A. Kroll Nitin Kohli Richmond Y. Wong 104 74 0 26 Sep 2019
Fair-by-design explainable models for prediction of recidivism Eduardo Soares Plamen Angelov FaML 48 23 0 18 Sep 2019
Advancing subgroup fairness via sleeping experts Avrim Blum Thodoris Lykouris FedML 68 37 0 18 Sep 2019
A Distributed Fair Machine Learning Framework with Private Demographic Data Protection Hui Hu Yijun Liu Zhen Wang Chao Lan FaML FedML 83 26 0 17 Sep 2019
Predictive Multiplicity in Classification Charles Marx Flavio du Pin Calmon Berk Ustun 136 147 0 14 Sep 2019
Learning Fair Rule Lists Ulrich Aïvodji Julien Ferry Sébastien Gambs Marie-José Huguet Mohamed Siala FaML 61 11 0 09 Sep 2019
Optimizing Generalized Rate Metrics through Game Equilibrium Harikrishna Narasimhan Andrew Cotter Maya R. Gupta 52 4 0 06 Sep 2019
Quantifying Infra-Marginality and Its Trade-off with Group Fairness Arpita Biswas Siddharth Barman Amit Deshpande Amit Sharma 32 3 0 03 Sep 2019
Fairness Warnings and Fair-MAML: Learning Fairly with Minimal Data Dylan Slack Sorelle A. Friedler Emile Givental FaML 118 55 0 24 Aug 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 603 4,424 0 23 Aug 2019
Data Management for Causal Algorithmic Fairness Babak Salimi B. Howe Dan Suciu CML FaML 41 23 0 20 Aug 2019
Towards Reducing Biases in Combining Multiple Experts Online Yi Sun Iván Díaz Alfredo Cuesta-Infante K. Veeramachaneni FaML 35 0 0 19 Aug 2019