Fairness Datasets

Fairness datasets are crucial for developing and evaluating machine learning models that avoid perpetuating or amplifying societal biases. Current research focuses on creating datasets representative of real-world scenarios, encompassing diverse demographic groups and incorporating various protected attributes, while also addressing challenges like data privacy and proxy variable usage. This work utilizes diverse model architectures, including deep neural networks and various fairness-aware learning algorithms, to assess and mitigate bias in applications ranging from job recommendations to medical image analysis. The development and rigorous evaluation of these datasets are essential for advancing fairness in AI and ensuring equitable outcomes across different populations.

Papers

October 25, 2024

FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs
Zhiting Fan, Ruizhe Chen, Tianxiang Hu, Zuozhu Liu
Language Model Multi Turn Dialogue Fairness Benchmark Fairness Datasets Conversational LLM

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

September 5, 2024

FairQuant: Certifying and Quantifying Fairness of Deep Neural Networks
Brian Hyeongseok Kim, Jingbo Wang, Chao Wang
Deep Neural Network Individual Fairness Fairness Property Fairness Datasets

July 24, 2024

Dataset Distribution Impacts Model Fairness: Single vs. Multi-Task Learning
Ralf Raumanns, Gerard Schouten, Josien P. W. Pluim, Veronika Cheplygina
Multi Task Learning Gender Bias Skin Lesion Single Label ResNet Based Fairness Datasets Adversarial Model

July 3, 2024

FairJob: A Real-World Dataset for Fairness in Online Systems
Mariia Vladimirova, Federico Pavone, Eustache Diemert
Procedural Fairness Algorithmic Fairness Biased Datasets Real World Dataset Fairness Datasets Fairness Toolkits Fair Utility

May 21, 2024

FairLENS: Assessing Fairness in Law Enforcement Speech Recognition
Yicheng Wang, Mark Cusick, Mohamed Laila, Kate Puech, Zhengping Ji, Xia Hu, Michael Wilson, Noah Spitzer-Williams, Bryan Wheeler, Yasser Ibrahim
Automatic Speech Recognition Procedural Fairness Automatic Speech Recognition Model Fairness Evaluation Fairness Datasets

February 27, 2024

FairBelief -- Assessing Harmful Beliefs in Language Models
Mattia Setzu, Marta Marchiori Manerba, Pasquale Minervini, Debora Nozza
Language Model Harmful Content Fairness Datasets

November 3, 2023

FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling
Yu Tian, Min Shi, Yan Luo, Ava Kouhana, Tobias Elze, Mengyu Wang
Segment Anything Model Segmentation Performance Fairness Datasets Fairness Learning Error Scaling

October 3, 2023

FairVision: Equitable Deep Learning for Eye Disease Screening via Fair Identity Scaling
Yan Luo, Muhammad Osama Khan, Yu Tian, Min Shi, Zehao Dou, Tobias Elze, Yi Fang, Mengyu Wang
Medical Image Fair Machine Learning Fair Algorithm Fairness Datasets Fair Inference Eye Disease Screening

July 31, 2023

A Suite of Fairness Datasets for Tabular Classification
Martin Hirzel, Michael Feffer
Procedural Fairness Machine Learning Classifier Fairness Aware Machine Software Suite Fairness Datasets Tabular Classification

February 24, 2023

Fairness in Language Models Beyond English: Gaps and Challenges
Krithika Ramesh, Sunayana Sitaram, Monojit Choudhury
Language Model Technical Challenge Procedural Fairness Multilingual Model Filling Gap Fair Credit Fairness Datasets

January 29, 2023

Preserving Fairness in AI under Domain Shift
Serban Stan, Mohammad Rostami
Artificial Intelligence Domain Shift AI Model Fair Model Annotated Training Data Fairness Datasets Fairness Verification

July 4, 2022

How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts
Haotao Wang, Junyuan Hong, Jiayu Zhou, Zhangyang Wang
Neural Network Procedural Fairness Distribution Shift Fairness Aware Machine Fairness Datasets Robust Fairness

May 20, 2022

CertiFair: A Framework for Certified Global Fairness of Neural Networks
Haitham Khedr, Yasser Shoukry
Neural Network New Framework Fairness Loss Fairness Property Fairness Datasets