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
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness Neil Menghani E. McFowland Daniel B. Neill 80 0 0 19 Jun 2023
Correcting Underrepresentation and Intersectional Bias for Classification Emily Diana A. Tolbert FaML 92 1 0 19 Jun 2023
Evaluating Superhuman Models with Consistency Checks Lukas Fluri Daniel Paleka Florian Tramèr ELM 196 48 0 16 Jun 2023
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods Xiaotian Han Jianfeng Chi Yu Chen Qifan Wang Han Zhao Na Zou Helen Zhou 133 35 0 15 Jun 2023
Arbitrariness Lies Beyond the Fairness-Accuracy Frontier Carol Xuan Long Hsiang Hsu Wael Alghamdi Flavio du Pin Calmon FaML 95 9 0 15 Jun 2023
Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairness Repair using AutoML Giang Nguyen Sumon Biswas Hridesh Rajan FaML 141 16 0 15 Jun 2023
Are fairness metric scores enough to assess discrimination biases in machine learning? Fanny Jourdan Laurent Risser Jean-Michel Loubes Nicholas M. Asher FaML 86 5 0 08 Jun 2023
Reconciling Predictive and Statistical Parity: A Causal Approach Drago Plečko Elias Bareinboim FaML 87 2 0 08 Jun 2023
Toward A Logical Theory Of Fairness and Bias Vaishak Belle FaML 159 1 0 08 Jun 2023
Doubly Constrained Fair Clustering John P. Dickerson Seyed-Alireza Esmaeili Jamie Morgenstern Claire Jie Zhang FaML 85 8 0 31 May 2023
Disentangling and Operationalizing AI Fairness at LinkedIn Joaquin Quiñonero Candela Yuwen Wu Brian Hsu Sakshi Jain Jennifer Ramos Jon Adams R. Hallman Kinjal Basu 138 9 0 30 May 2023
Examining risks of racial biases in NLP tools for child protective services Anjalie Field Amanda Coston Nupoor Gandhi Alexandra Chouldechova Emily Putnam-Hornstein David Steier Yulia Tsvetkov 94 16 0 30 May 2023
Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making Timothée Schmude Laura M. Koesten Torsten Moller Sebastian Tschiatschek 75 1 0 26 May 2023
Monitoring Algorithmic Fairness T. Henzinger Mahyar Karimi Konstantin Kueffner Kaushik Mallik FaML 84 10 0 25 May 2023
Deep Learning and Ethics Travis LaCroix Simon J. D. Prince FaML 102 0 0 24 May 2023
Time Fairness in Online Knapsack Problems Adam Lechowicz Rik Sengupta Bo Sun Shahin Kamali Mohammad Hajiesmaili FaML 131 4 0 22 May 2023
Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree Hilde J. P. Weerts Raphaële Xenidis Fabien Tarissan Henrik Palmer Olsen Mykola Pechenizkiy FaML 95 27 0 05 May 2023
MLHOps: Machine Learning for Healthcare Operations Kristoffer Larsen Vallijah Subasri A. Krishnan Cláudio Tinoco Mesquita Diana Paez Laleh Seyyed-Kalantari Amalia Peix LM&MA AI4TS VLM 115 3 0 04 May 2023
On the Impact of Data Quality on Image Classification Fairness Aki Barry Lei Han Gianluca Demartini 115 5 0 02 May 2023
Coarse race data conceals disparities in clinical risk score performance Rajiv Movva Divya Shanmugam Kaihua Hou P. Pathak John Guttag Nikhil Garg Emma Pierson 94 22 0 18 Apr 2023
Maximal Fairness Marybeth Defrance Tijl De Bie 87 9 0 12 Apr 2023
Learning Optimal Fair Scoring Systems for Multi-Class Classification Julien Rouzot Julien Ferry Marie-José Huguet FaML 216 11 0 11 Apr 2023
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks Yuzhen Mao Zhun Deng Huaxiu Yao Ting Ye Kenji Kawaguchi James Zou 136 23 0 08 Apr 2023
Towards Inclusive Fairness Evaluation via Eliciting Disagreement Feedback from Non-Expert Stakeholders Mukund Telukunta Venkata Sriram Siddhardh Nadendla 69 1 0 07 Apr 2023
Fairness through Aleatoric Uncertainty Anique Tahir Lu Cheng Huan Liu 120 16 0 07 Apr 2023
Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa M. Asiedu Awa Dieng Abigail Oppong Margaret Nagawa Sanmi Koyejo Katherine A. Heller 132 13 0 05 Apr 2023
Towards "Anytime, Anywhere" Community Learning and Engagement around the Design of Public Sector AI Wesley Hanwen Deng Motahhare Eslami Kenneth Holstein 95 1 0 31 Mar 2023
Bias mitigation techniques in image classification: fair machine learning in human heritage collections Dalia Ortiz Pablo Sushruth Badri Erik Norén Christoph Nötzli 86 1 0 20 Mar 2023
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML Hilde J. P. Weerts Florian Pfisterer Matthias Feurer Katharina Eggensperger Eddie Bergman Noor H. Awad Joaquin Vanschoren Mykola Pechenizkiy B. Bischl Frank Hutter FaML 117 20 0 15 Mar 2023
Graph Neural Network Surrogates of Fair Graph Filtering Emmanouil Krasanakis Symeon Papadopoulos 94 1 0 14 Mar 2023
Beyond Demographic Parity: Redefining Equal Treatment Carlos Mougan Laura State Antonio Ferrara Salvatore Ruggieri Steffen Staab FaML 140 1 0 14 Mar 2023
No-regret Algorithms for Fair Resource Allocation Abhishek Sinha Ativ Joshi Rajarshi Bhattacharjee Cameron Musco Mohammad Hajiesmaili FaML 98 8 0 11 Mar 2023
Fairness-enhancing deep learning for ride-hailing demand prediction Yunhan Zheng Qingyi Wang Dingyi Zhuang Shenhao Wang Jinhua Zhao 128 13 0 10 Mar 2023
SoK: Content Moderation for End-to-End Encryption Sarah Scheffler Jonathan R. Mayer 128 26 0 07 Mar 2023
Towards Algorithmic Fairness by means of Instance-level Data Re-weighting based on Shapley Values Adrián Arnaiz-Rodríguez Nuria Oliver FedML TDI 116 2 0 03 Mar 2023
Feature Importance Disparities for Data Bias Investigations Peter W. Chang Leor Fishman Seth Neel 132 2 0 03 Mar 2023
Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness Zahra Ashktorab Benjamin Hoover Mayank Agarwal Casey Dugan Werner Geyer Han Yang Mikhail Yurochkin FaML 126 18 0 01 Mar 2023
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization Sangwon Jung Taeeon Park Sanghyuk Chun Taesup Moon 86 21 0 01 Mar 2023
How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations? Fanny Jourdan Titon Tshiongo Kaninku Nicholas M. Asher Jean-Michel Loubes Laurent Risser FaML 83 5 0 27 Feb 2023
Designing Equitable Algorithms Alex Chohlas-Wood Madison Coots Sharad Goel Julian Nyarko FaML 60 16 0 17 Feb 2023
On (assessing) the fairness of risk score models Eike Petersen M. Ganz Sune Holm Aasa Feragen FaML 97 24 0 17 Feb 2023
The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction Falaah Arif Khan Julia Stoyanovich FaML VLM CML 35 3 0 17 Feb 2023
Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers Melissa Hall Bobbie Chern Laura Gustafson Denisse Ventura Harshad Kulkarni Candace Ross Nicolas Usunier 95 6 0 16 Feb 2023
On the Impact of Explanations on Understanding of Algorithmic Decision-Making Timothée Schmude Laura M. Koesten Torsten Moller Sebastian Tschiatschek 132 18 0 16 Feb 2023
Individual Fairness under Uncertainty Wenbin Zhang Zichong Wang Juyong Kim Cheng Cheng Thomas Oommen Pradeep Ravikumar Jeremy C. Weiss FaML 120 14 0 16 Feb 2023
Provable Detection of Propagating Sampling Bias in Prediction Models Pavan Ravishankar Qingyu Mo E. McFowland Daniel B. Neill 86 6 0 13 Feb 2023
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice Andrew Bell Lucius E.J. Bynum Nazarii Drushchak Tetiana Herasymova Lucas Rosenblatt Julia Stoyanovich 81 23 0 13 Feb 2023
Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLP Xudong Han Timothy Baldwin Trevor Cohn 96 12 0 11 Feb 2023
An Epistemic and Aleatoric Decomposition of Arbitrariness to Constrain the Set of Good Models Falaah Arif Khan Denys Herasymuk Nazar Protsiv Julia Stoyanovich 69 3 0 09 Feb 2023
Local Law 144: A Critical Analysis of Regression Metrics Giulio Filippi Sara Zannone Airlie Hilliard Adriano Soares Koshiyama MLAU 36 3 0 08 Feb 2023