datamllab/awesome-fairness-in-ai
A curated list of awesome Fairness in AI resources
This resource helps anyone developing or deploying AI systems ensure their models are fair and unbiased. It provides a curated list of research papers and resources covering various aspects of algorithmic fairness, from theoretical understandings and fairness measurements to bias detection and mitigation strategies. Researchers, data scientists, and AI ethicists can use this to understand, identify, and reduce discrimination in AI.
332 stars. No commits in the last 6 months.
Use this if you are developing AI models and want to learn how to identify and mitigate biases to ensure fair and equitable outcomes for all user groups.
Not ideal if you are looking for ready-to-use software tools or code to directly implement fairness techniques without diving into academic research.
Stars
332
Forks
65
Language
—
License
MIT
Category
Last pushed
Sep 15, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/datamllab/awesome-fairness-in-ai"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
fairlearn/fairlearn
A Python package to assess and improve fairness of machine learning models.
Trusted-AI/AIF360
A comprehensive set of fairness metrics for datasets and machine learning models, explanations...
microsoft/responsible-ai-toolbox
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment...
holistic-ai/holisticai
This is an open-source tool to assess and improve the trustworthiness of AI systems.
EFS-OpenSource/Thetis
Service to examine data processing pipelines (e.g., machine learning or deep learning pipelines)...