Popular GitHub Repositories for Fairness Ai

? Open-Source Evaluation & Testing for AI & LLM systems

A Python package to assess and improve fairness of machine learning models.

WEFE: The Word Embeddings Fairness Evaluation Framework. WEFE is a framework that standardizes the bias measurement and mitigation in Word Embeddings models. Please feel welcome to open an issue in case you have any questions or a pull request if you want to contribute to the project!

The LinkedIn Fairness Toolkit (LiFT) is a Scala/Spark library that enables the measurement of fairness in large scale machine learning workflows.

Safety Score for Pre-Trained Language Models

FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)

Papers and online resources related to machine learning fairness

Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models.

A curated list of awesome academic research, books, code of ethics, data sets, institutes, maturity models, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible, Trustworthy, and Human-Centered AI.

PyTorch package to train and audit ML models for Individual Fairness

[ACL 2020] Towards Debiasing Sentence Representations

? Influenciae is a Tensorflow Toolbox for Influence Functions

[ICML 2021] Towards Understanding and Mitigating Social Biases in Language Models

[ACM 2024] Jurity: Fairness & Evaluation Library

Credo AI Lens is a comprehensive assessment framework for AI systems. Lens standardizes model and data assessment, and acts as a central gateway to assessments created in the open source community.

A tool for gender bias identification in text. Part of Microsoft's Responsible AI toolbox.

Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice

EMNLP'2022: BERTScore is Unfair: On Social Bias in Language Model-Based Metrics for Text Generation

R package for computing and visualizing fair ML metrics

Counterfactual Local Explanations of AI systems