Procedural Fairness

Procedural fairness in artificial intelligence focuses on ensuring that AI systems make decisions equitably across different demographic groups, mitigating biases that can lead to discriminatory outcomes. Current research emphasizes developing and evaluating fairness-aware algorithms and models, including those based on adversarial learning, data augmentation techniques like mixup, and distributionally robust optimization, across various applications like healthcare, process analytics, and recommender systems. This research is crucial for building trustworthy AI systems and addressing societal concerns about algorithmic bias, impacting both the development of ethical AI guidelines and the practical deployment of AI in sensitive domains.

Papers

May 18, 2023

In the Name of Fairness: Assessing the Bias in Clinical Record De-identification
Yuxin Xiao, Shulammite Lim, Tom Joseph Pollard, Marzyeh Ghassemi
Procedural Fairness Absolute Stance Bias Clinical Note Clinical Data Name Translation De Identification

May 12, 2023

Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation
Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He
Language Model Procedural Fairness Effective Recommendation LLM Benchmark Traditional Recommender Fairness Benchmark Novel Recommendation

May 11, 2023

May 8, 2023

Runtime Monitoring of Dynamic Fairness Properties
Thomas A. Henzinger, Mahyar Karimi, Konstantin Kueffner, Kaushik Mallik
Procedural Fairness Runtime Monitoring Dynamic Fairness Fairness Toolkits

May 6, 2023

Fairness in Image Search: A Study of Occupational Stereotyping in Image Retrieval and its Debiasing
Swagatika Dash
Procedural Fairness Gender Bias Image Retrieval Self Debiasing Image Search Content Based Image Retrieval Relevance Score

May 5, 2023

A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness
Zongxiong Chen, Jiahui Geng, Derui Zhu, Herbert Woisetschlaeger, Qing Li, Sonja Schimmler, Ruben Mayer, Chunming Rong
Native Robustness Procedural Fairness System Performance Membership Inference Attack Privacy Policy Dataset Distillation Small Datasets

May 4, 2023

Integrating Psychometrics and Computing Perspectives on Bias and Fairness in Affective Computing: A Case Study of Automated Video Interviews
Brandon M Booth, Louis Hickman, Shree Krishna Subburaj, Louis Tay, Sang Eun Woo, Sidney K. DMello
Procedural Fairness Absolute Stance Bias Affective Computing Human Emotion Psychometric Property

May 3, 2023

Fairness in AI Systems: Mitigating gender bias from language-vision models
Lavisha Aggarwal, Shruti Bhargava
Procedural Fairness Gender Bias AI System Inherent Bias Biased Data Language Vision Model

May 2, 2023

Fairness and representation in satellite-based poverty maps: Evidence of urban-rural disparities and their impacts on downstream policy
Emily Aiken, Esther Rolf, Joshua Blumenstock
Procedural Fairness Individual Representation Bias Evaluation Impact Assessment Health Disparity Poverty Map

May 1, 2023

Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity
Josh Gardner, Renzhe Yu, Quan Nguyen, Christopher Brooks, Rene Kizilcec
Procedural Fairness Model Performance Future Implication Model Fairness Zero Shot Transfer Intersectional Fairness Teaching Model

April 26, 2023

Towards clinical AI fairness: A translational perspective
Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Mayli Mertens, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Ravi Chandran Narrendar, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu
Artificial Intelligence Procedural Fairness AI Fairness Clinical Language

April 25, 2023

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

April 18, 2023

Generative models improve fairness of medical classifiers under distribution shifts
Ira Ktena, Olivia Wiles, Isabela Albuquerque, Sylvestre-Alvise Rebuffi, Ryutaro Tanno, Abhijit Guha Roy, Shekoofeh Azizi, Danielle Belgrave, Pushmeet Kohli, Alan Karthikesalingam, Taylan Cemgil, Sven Gowal
Generative Model Procedural Fairness Domain Generalization Distribution Shift Medical Imaging Soft Augmentation Model Bias

April 16, 2023

Fairness in AI and Its Long-Term Implications on Society
Ondrej Bohdal, Timothy Hospedales, Philip H. S. Torr, Fazl Barez
Artificial Intelligence Procedural Fairness Model Bias Future Implication AI Fairness Societal Domain Biased Prediction

April 14, 2023

April 10, 2023

FairPilot: An Explorative System for Hyperparameter Tuning through the Lens of Fairness
Francesco Di Carlo, Nazanin Nezami, Hadis Anahideh, Abolfazl Asudeh
Machine Learning Machine Learning Model Procedural Fairness Camera Lens New Hyperparameter

Procedural Fairness

Papers

In the Name of Fairness: Assessing the Bias in Clinical Record De-identification

Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation

A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges

Fairness in Machine Learning meets with Equity in Healthcare

Runtime Monitoring of Dynamic Fairness Properties

Fairness in Image Search: A Study of Occupational Stereotyping in Image Retrieval and its Debiasing

A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness

Integrating Psychometrics and Computing Perspectives on Bias and Fairness in Affective Computing: A Case Study of Automated Video Interviews

Fairness in AI Systems: Mitigating gender bias from language-vision models

Fairness and representation in satellite-based poverty maps: Evidence of urban-rural disparities and their impacts on downstream policy

Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity

Towards clinical AI fairness: A translational perspective

(Local) Differential Privacy has NO Disparate Impact on Fairness

Fairness and Bias in Truth Discovery Algorithms: An Experimental Analysis

ACROCPoLis: A Descriptive Framework for Making Sense of Fairness

Generative models improve fairness of medical classifiers under distribution shifts

Fairness in AI and Its Long-Term Implications on Society

Fairness in Visual Clustering: A Novel Transformer Clustering Approach

FairRec: Fairness Testing for Deep Recommender Systems

FairPilot: An Explorative System for Hyperparameter Tuning through the Lens of Fairness