Discover and explore the most popular open source AI and machine learning tools from GitHub
⬛ Python Individual Conditional Expectation Plot Toolbox
Comparing fairness-aware machine learning techniques.
The official Syft worker for Web and Node, built in Javascript
Research code for auditing and exploring black box machine-learning models.
A library that implements fairness-aware machine learning algorithms
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets --- https://arxiv.org/abs/2004.07999
Themis™ is a software fairness tester.
Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰
Modular Python Toolbox for Fairness, Accountability and Transparency Forensics
PyTorch implementation of parity loss as constraints function to realize the fairness of machine learning.
Differential privacy for computer vision
Testing tool for discovering unfair bias in machine learning models
Building a responsible AI marketplace is a community effort. We're grateful to the developers, researchers, organizations, evaluators, and individuals whose work helps make AI more accessible, transparent, and responsible through the framework of 6 pillars:
Researchers and developers whose data collection efforts help build the foundation of AI tools.
Responsible AI Marketplace Open-source AI Tools Database
Cornell University
Advisor: Martin Wells
Contributors: Houlin Chen, Xinyu Zhu, Yinghan Xia, Kate Chanpong, Zixuan Huangfu
Responsible AI depends on meaningful evaluation, testing, research, and transparency.
Credits, resources and support.
Core technologies powering the marketplace.
Our marketplace is strengthened by the people who review, test, evaluate, document, and share their experiences with AI tools. Thank you to everyone who contributes their time, expertise, and perspective.
If you use this database in your research, please use the following BibTeX entry.
@misc{ai2030-marketplace,
title={AI2030 Responsible AI Open-Source Tools and Commercial Tools Database / Marketplace},
author={AI2030 and Community Contributors},
year={2025--2026},
url={https://marketplace.ai2030.org}
}A Note on Independence — Recognition on this page does not constitute an endorsement of a tool, organization, model, or viewpoint. Commercial relationships and sponsorships are disclosed where applicable. Marketplace listings, evaluations, and editorial materials are governed by our published standards and policies.