Fairness Measure

Fairness measures in machine learning and decision-making aim to quantify and mitigate bias, ensuring equitable outcomes across different demographic groups. Current research focuses on developing new metrics that account for uncertainty in predictions, handle multiple sensitive attributes, and address the incompatibility between various fairness criteria, often employing manifold-based approaches or statistical equivalence testing. These advancements are crucial for building trustworthy AI systems and promoting fairness in high-stakes applications like loan approvals, hiring processes, and biometric authentication, ultimately impacting the ethical deployment of AI in society.

Papers

January 25, 2023

Increasing Fairness via Combination with Learning Guarantees
Yijun Bian, Kun Zhang, Anqi Qiu, Nanguang Chen
Procedural Fairness Group Fairness New Combination Fairness Measure Learning Guarantee

November 21, 2022

Bursting the Burden Bubble? An Assessment of Sharma et al.'s Counterfactual-based Fairness Metric
Yochem van Rosmalen, Florian van der Steen, Sebastiaan Jans, Daan van der Weijden
Procedural Fairness Direct Assessment Decision Boundary Novel Metric Fairness Measure Categorical Burden Score Statistical Parity

October 30, 2022

Mitigating Unfairness via Evolutionary Multi-objective Ensemble Learning
Zhang Qingquan, Liu Jialin, Zhang Zeqi, Wen Junyi, Mao Bifei, Yao Xin
Fairness Metric Fairness Measure Fairness Mitigation Multiple Fairness Metric

October 9, 2022

A Differentiable Distance Approximation for Fairer Image Classification
Nicholas Rosa, Tom Drummond, Mehrtash Harandi
Absolute Stance Bias Artificial Intelligence Model AI Model Fairness Measure Differentiable Function

September 16, 2022

Survey on Fairness Notions and Related Tensions
Guilherme Alves, Fabien Bernier, Miguel Couceiro, Karima Makhlouf, Catuscia Palamidessi, Sami Zhioua
Timely Survey Fairness Notion Fairness Accuracy Conflict Classification Fairness Measure Fairness Benchmark Datasets

June 29, 2022

AFAFed -- Protocol analysis
Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh, Sima Sarv Ahrabi
Convergence Rate Asynchronous Federated Learning Fairness Measure Convergence Property Protocol Analysis

June 13, 2022

A Machine Learning Model for Predicting, Diagnosing, and Mitigating Health Disparities in Hospital Readmission
Shaina Raza
Machine Learning Model Human Prediction Medical Diagnosis Clinical Data Health Disparity Healthcare Datasets Fairness Measure Fair Prediction Hospital Readmission

May 23, 2022

Fairness in Recommender Systems: Research Landscape and Future Directions
Yashar Deldjoo, Dietmar Jannach, Alejandro Bellogin, Alessandro Difonzo, Dario Zanzonelli
Recommender System Procedural Fairness Effective Recommendation Future Direction Movie Recommendation Research Trend Fairness Measure

February 25, 2022

Exploring Fairness in District-based Multi-party Elections under different Voting Rules using Stochastic Simulations
Adway Mitra
Procedural Fairness Fairness Measure Voting Rule Electoral Process Stochastic Simulation District Based Election