Individual Fairness

Individual fairness in machine learning aims to ensure that similar individuals are treated similarly by algorithms, regardless of protected attributes like race or gender, addressing a critical ethical concern in AI. Current research focuses on developing methods to certify and quantify individual fairness within various model architectures, including deep neural networks and graph neural networks, often employing techniques like reweighting, adversarial training, and metric learning to achieve this goal. This work is significant because it strives to create more equitable and trustworthy AI systems, impacting both the theoretical understanding of fairness and the practical deployment of AI in sensitive applications.

Papers

April 21, 2023

Individual Fairness in Bayesian Neural Networks
Alice Doherty, Matthew Wicker, Luca Laurenti, Andrea Patane
Bayesian Neural Network Individual Fairness Fairness Aware Fairness Benchmark

April 19, 2023

Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness
Edward A. Small, Kacper Sokol, Daniel Manning, Flora D. Salim, Jeffrey Chan
Group Fairness Post Processing Group Setting Relative Probability Individual Fairness Equalized Odds

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

Individual Fairness under Uncertainty
Wenbin Zhang, Zichong Wang, Juyong Kim, Cheng Cheng, Thomas Oommen, Pradeep Ravikumar, Jeremy Weiss
High Uncertainty Anticipation Model Fairness Algorithmic Bias Individual Fairness Fairness Research

February 8, 2023

Fairness in Matching under Uncertainty
Siddartha Devic, David Kempe, Vatsal Sharan, Aleksandra Korolova
Procedural Fairness High Uncertainty Anticipation Matching Accuracy Individual Fairness Algorithmic Decision Two Sided Reward Ambiguity Fair Utility

February 4, 2023

Matrix Estimation for Individual Fairness
Cindy Y. Zhang, Sarah H. Cen, Devavrat Shah
Algorithmic Fairness Individual Fairness Fairness Performance Trade Matrix Estimation

January 30, 2023

Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks
He Zhang, Xingliang Yuan, Shirui Pan
Graph Neural Network Privacy Risk Individual Fairness GNN Performance Fair GNN Trustworthy Graph Graph Privacy

January 19, 2023

Individual Fairness for Social Media Influencers
Stefania Ionescu, Nicolo Pagan, Aniko Hannak
Recommender System Recommendation Model Individual Fairness Content Creator Content Quality

November 29, 2022

Learning Antidote Data to Individual Unfairness
Peizhao Li, Ethan Xia, Hongfu Liu
Adversarial Perturbation Distributionally Robust Optimization Fairness Notion Individual Fairness Fairness Objective

November 11, 2022

Identifying, measuring, and mitigating individual unfairness for supervised learning models and application to credit risk models
Rasoul Shahsavarifar, Jithu Chandran, Mario Inchiosa, Amit Deshpande, Mario Schlener, Vishal Gossain, Yara Elias, Vinaya Murali
Application Proficiency Supervised Learning Group Fairness Individual Fairness Fairness Property Fairness Mitigation Credit Risk Model

October 10, 2022

fAux: Testing Individual Fairness via Gradient Alignment
Giuseppe Castiglione, Ga Wu, Christopher Srinivasa, Simon Prince
Machine Learning Model Procedural Fairness Group DIscrimination Individual Fairness Gradient Alignment Domain Sample

September 15, 2022

iFlipper: Label Flipping for Individual Fairness
Hantian Zhang, Ki Hyun Tae, Jaeyoung Park, Xu Chu, Steven Euijong Whang
Procedural Fairness Individual Fairness Fairness Property Label Flipping

September 8, 2022

Analyzing the Effect of Sampling in GNNs on Individual Fairness
Rebecca Salganik, Fernando Diaz, Golnoosh Farnadi
Recommender System Mixed Effect Graph Convolutional Network Bias Mitigation Gene Level GNN Open Sampling Individual Fairness Downstream Forecasting Task

August 21, 2022

Individual Fairness under Varied Notions of Group Fairness in Bipartite Matching - One Framework to Approximate Them All
Atasi Panda, Anand Louis, Prajakta Nimbhorkar
New Framework Group Fairness Fairness Constraint Individual Fairness Group Fairness Constraint

July 16, 2022

Characterization of Group-Fair Social Choice Rules under Single-Peaked Preferences
Gogulapati Sreedurga, Soumyarup Sadhukhan, Souvik Roy, Yadati Narahari
Group Fairness New Characterization Individual Fairness Social Choice Single Peaked Preference

May 18, 2022

Accurate Fairness: Improving Individual Fairness without Trading Accuracy
Xuran Li, Peng Wu, Jing Su
AI Fairness Individual Fairness Robust Fairness

May 11, 2022

Individual Fairness Guarantees for Neural Networks
Elias Benussi, Andrea Patane, Matthew Wicker, Luca Laurenti, Marta Kwiatkowska
Neural Network Individual Fairness Fairness Benchmark Fairness Guarantee Variance Tolerance Factor

May 1, 2022

Domain Adaptation meets Individual Fairness. And they get along
Debarghya Mukherjee, Felix Petersen, Mikhail Yurochkin, Yuekai Sun
Domain Adaptation Distribution Shift Algorithmic Fairness Algorithmic Bias Individual Fairness Fairness Intervention