Fairness Criterion

Fairness criteria in machine learning and decision-making aim to define and achieve equitable outcomes across different groups, mitigating biases that may lead to unfair or discriminatory results. Current research focuses on developing and comparing various fairness metrics (e.g., demographic parity, equalized odds), exploring their limitations (especially in dynamic or long-term contexts), and designing algorithms (including pre-processing, in-training, and post-processing methods) to satisfy these criteria. This field is crucial for ensuring responsible use of AI systems in high-stakes applications like criminal justice, loan applications, and resource allocation, impacting both the ethical development of AI and the fairness of societal systems.

Papers

November 2, 2024

Federated Learning with Relative Fairness
Shogo Nakakita, Tatsuya Kaneko, Shinya Takamaeda-Yamazaki, Masaaki Imaizumi
Federated Learning Robust Optimization Convergence Rate Fairness Objective Proportional Fairness Fairness Criterion

October 23, 2024

Learning Fair and Preferable Allocations through Neural Network
Ryota Maruo, Koh Takeuchi, Hisashi Kashima
Neural Network Fairness Constraint Fairness Notion Fair Learning Fairness Criterion Fair Allocation Efficient Allocation

October 3, 2024

Harm Ratio: A Novel and Versatile Fairness Criterion
Soroush Ebadian, Rupert Freeman, Nisarg Shah
Long Form Novel Fairness Criterion Envy Free

August 24, 2024

Ensuring Fairness with Transparent Auditing of Quantitative Bias in AI Systems
Chih-Cheng Rex Yuan, Bow-Yaw Wang
AI System AI Fairness Achieving Fairness Fairness Criterion

June 10, 2024

Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges
Usman Gohar, Zeyu Tang, Jialu Wang, Kun Zhang, Peter L. Spirtes, Yang Liu, Lu Cheng
Machine Learning Timely Survey Technical Challenge Fairness Assessment Long Term Fairness Fairness Criterion Fairness Implication

May 24, 2024

Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making
Drago Plecko, Elias Bareinboim
Human Prediction Decision Making Fair Machine Learning Fairness Criterion Bias Amplification Causal Concept

February 9, 2024

Value-based Resource Matching with Fairness Criteria: Application to Agricultural Water Trading
Abhijin Adiga, Yohai Trabelsi, Tanvir Ferdousi, Madhav Marathe, S. S. Ravi, Samarth Swarup, Anil Kumar Vullikanti, Mandy L. Wilson, Sarit Kraus, Reetwika Basu, Supriya Savalkar, Matthew Yourek, Michael Brady, Kirti Rajagopalan, Jonathan Yoder
Application Proficiency Two Sided Fairness Criterion Constrained Environment Optimal Allocation Crop Diversification

October 31, 2023

September 7, 2023

Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
Yuancheng Xu, Chenghao Deng, Yanchao Sun, Ruijie Zheng, Xiyao Wang, Jieyu Zhao, Furong Huang
Long Term Bias Mitigation Sequential Decision Long Term Fairness Fairness Criterion

June 1, 2023

Unfair Utilities and First Steps Towards Improving Them
Frederik Hytting Jørgensen, Sebastian Weichwald, Jonas Peters
Procedural Fairness Fairness Criterion First Step

March 15, 2023

DualFair: Fair Representation Learning at Both Group and Individual Levels via Contrastive Self-supervision
Sungwon Han, Seungeon Lee, Fangzhao Wu, Sundong Kim, Chuhan Wu, Xiting Wang, Xing Xie, Meeyoung Cha
Self Supervised Group Fairness Group Setting Counterfactual Fairness Multiple Level Fair Representation Learning Fairness Criterion Contrastive Self Supervision

March 3, 2023

A toolkit of dilemmas: Beyond debiasing and fairness formulas for responsible AI/ML
Andrés Domínguez Hernández, Vassilis Galanos
Machine Learning Responsible AI Easy to Use Toolkit Ethical AI Emotional Dilemma Fairness Criterion

November 3, 2022

Fair and Optimal Classification via Post-Processing
Ruicheng Xian, Lang Yin, Han Zhao
Face Recognition FAir Classifier Optimal Classifier Fair Algorithm Fairness Criterion Optimal Fair

September 21, 2022

Fairness Reprogramming
Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang
Fairness Perception Fairness Criterion

September 20, 2022

Fairness and robustness in anti-causal prediction
Maggie Makar, Alexander D'Amour
Native Robustness Procedural Fairness Causal Structure Causal Prediction Fairness Criterion Fairness Mitigation

July 12, 2022

Long Term Fairness for Minority Groups via Performative Distributionally Robust Optimization
Liam Peet-Pare, Nidhi Hegde, Alona Fyshe
Machine Learning Distributionally Robust Optimization Performative Prediction Fairness Research Long Term Fairness Fairness Criterion Minority Group

May 31, 2022

Social Bias Meets Data Bias: The Impacts of Labeling and Measurement Errors on Fairness Criteria
Yiqiao Liao, Parinaz Naghizadeh
Social Bias Dataset Bias Manual Label Biased Data Fairness Criterion Prediction Bias Measurement Error

May 4, 2022

fairlib: A Unified Framework for Assessing and Improving Classification Fairness
Xudong Han, Aili Shen, Yitong Li, Lea Frermann, Timothy Baldwin, Trevor Cohn
Unified Framework Debiasing Method Fairness Evaluation Fairness Criterion

February 23, 2022

Fairness-Aware Naive Bayes Classifier for Data with Multiple Sensitive Features
Stelios Boulitsakis-Logothetis
Raw Data Fairness Aware Machine Fairness Aware Naive Bayes Proportional Fairness Fairness Criterion Protected Attribute