Fairness Assessment

Fairness assessment in machine learning aims to identify and mitigate biases in algorithms, ensuring equitable outcomes across different demographic groups. Current research focuses on developing and applying fairness metrics, particularly for complex models like graph neural networks and large language models, and exploring various bias mitigation techniques such as post-processing and fairness-aware training. This work is crucial for building trustworthy and responsible AI systems, impacting fields ranging from healthcare and finance to criminal justice, where algorithmic bias can have significant societal consequences. The development of standardized evaluation methods and open-source auditing tools is also a key area of focus.

Papers

October 31, 2024

Monitoring fairness in machine learning models that predict patient mortality in the ICU
Tempest A. van Schaik, Xinggang Liu, Louis Atallah, Omar Badawi
Machine Learning Model Procedural Fairness Intensive Care Unit Fairness Assessment Year Specific Mortality Surface Biased Data

October 12, 2024

The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
Jake Fawkes, Nic Fishman, Mel Andrews, Zachary C. Lipton
LeArning Abstract Procedural Fairness Fairness Aware Machine Fairness Assessment Fairness Measure Fairness Datasets

October 8, 2024

FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applications
Nga Pham, Minh Kha Do, Tran Vu Dai, Pham Ngoc Hung, Anh Nguyen-Duc
Machine Learning Machine Learning Model Procedural Fairness Regression Model Fairness Assessment Educational Application

August 31, 2024

Multi-Output Distributional Fairness via Post-Processing
Gang Li, Qihang Lin, Ayush Ghosh, Tianbao Yang
Fairness Assessment Multi Output Regression

August 28, 2024

Using Backbone Foundation Model for Evaluating Fairness in Chest Radiography Without Demographic Data
Dilermando Queiroz, André Anjos, Lilian Berton
Bias Mitigation Fairness Assessment Fairness Analysis Demographic Data Equitable Healthcare System

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

June 9, 2024

Why Don't Prompt-Based Fairness Metrics Correlate?
Abdelrahman Zayed, Goncalo Mordido, Ioana Baldini, Sarath Chandar
Fairness Metric Fairness Assessment Statistical Fairness Term Fairness

January 8, 2024

Unveiling Bias in Fairness Evaluations of Large Language Models: A Critical Literature Review of Music and Movie Recommendation Systems
Chandan Kumar Sah, Dr. Lian Xiaoli, Muhammad Mirajul Islam
Critical Review Fairness Evaluation Fairness Assessment Movie Recommendation System

September 25, 2023

Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction
Yuning Du, Yuyang Xue, Rohan Dharmakumar, Sotirios A. Tsaftaris
Deep Learning Image Reconstruction Fairness Evaluation Fairness Assessment Based Magnetic Resonance Imaging Reconstruction Reconstruction Metric

September 20, 2023

Fairness Hub Technical Briefs: AUC Gap
Jinsook Lee, Chris Brooks, Renzhe Yu, Rene Kizilcec
Absolute Stance Bias Model Bias Fairness Assessment AUC Metric Fairness Toolkits Intersectional Group

August 1, 2023

Fair Models in Credit: Intersectional Discrimination and the Amplification of Inequity
Savina Kim, Stefan Lessmann, Galina Andreeva, Michael Rovatsos
Algorithmic Bias Fair Model Fairness Assessment Intersectional Social Attribute Consumer Credit

July 6, 2023

Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching
Nima Shahbazi, Nikola Danevski, Fatemeh Nargesian, Abolfazl Asudeh, Divesh Srivastava
Global Evaluation Procedural Fairness Social Medium Entity Matching Fairness Assessment Experimental Analysis Machine Bias

July 3, 2023

Unbiased Pain Assessment through Wearables and EHR Data: Multi-attribute Fairness Loss-based CNN Approach
Sharmin Sultana, Md Mahmudur Rahman, Atqiya Munawara Mahi, Shao-Hsien Liu, Mohammad Arif Ul Alam
Artificial Intelligence Convolutional Neural Network Wearable Device Patient Data Fairness Assessment Fairness Loss Pain Assessment

June 19, 2023

Fairness Index Measures to Evaluate Bias in Biometric Recognition
Ketan Kotwal, Sebastien Marcel
Absolute Stance Bias Biometric Identification Fairness Assessment Fairness Measure Demographic Fairness Multiple Fairness Metric

May 25, 2023

GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint
Paiheng Xu, Yuhang Zhou, Bang An, Wei Ai, Furong Huang
Graph Neural Network Algorithmic Fairness GNN Model Fair Representation Individual Fairness Fairness Assessment

April 19, 2023

ACROCPoLis: A Descriptive Framework for Making Sense of Fairness
Andrea Aler Tubella, Dimitri Coelho Mollo, Adam Dahlgren Lindström, Hannah Devinney, Virginia Dignum, Petter Ericson, Anna Jonsson, Timotheus Kampik, Tom Lenaerts, Julian Alfredo Mendez, Juan Carlos Nieves
Procedural Fairness Algorithmic Fairness Multiple Sens Fairness Assessment

March 26, 2023

FairGAT: Fairness-aware Graph Attention Networks
O. Deniz Kose, Yanning Shen
Graph Neural Network Graph Attention Network Group Fairness Algorithmic Bias Fairness Assessment

March 13, 2023

Are Models Trained on Indian Legal Data Fair?
Sahil Girhepuje, Anmol Goel, Gokul S Krishnan, Shreya Goyal, Satyendra Pandey, Ponnurangam Kumaraguru, Balaraman Ravindran
Full Model Algorithmic Bias Fairness Assessment Indian Legal Judgment Prediction

March 1, 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, Hao Bang Yang, Mikhail Yurochkin
Text Classification Group Fairness Model Fairness Algorithmic Bias Individual Fairness Individual Perspective Fairness Evaluation Fairness Assessment

February 16, 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
Computer Vision Vision Model Multi Label Image Classification Fairness Assessment

Fairness Assessment

Papers

Monitoring fairness in machine learning models that predict patient mortality in the ICU

The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning

FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applications

Multi-Output Distributional Fairness via Post-Processing

Using Backbone Foundation Model for Evaluating Fairness in Chest Radiography Without Demographic Data

Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges

Why Don't Prompt-Based Fairness Metrics Correlate?

Unveiling Bias in Fairness Evaluations of Large Language Models: A Critical Literature Review of Music and Movie Recommendation Systems

Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction

Fairness Hub Technical Briefs: AUC Gap

Fair Models in Credit: Intersectional Discrimination and the Amplification of Inequity

Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching

Unbiased Pain Assessment through Wearables and EHR Data: Multi-attribute Fairness Loss-based CNN Approach

Fairness Index Measures to Evaluate Bias in Biometric Recognition

GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint

ACROCPoLis: A Descriptive Framework for Making Sense of Fairness

FairGAT: Fairness-aware Graph Attention Networks

Are Models Trained on Indian Legal Data Fair?

Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness

Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers