The resource provides a list and a geographical worl map pointing ethical principle declarations and documents

A guide and toolkit for broader public and business leaders to consider not only AI fairness but also business strategy, governance and responsibility.

The toolkit presents key risks associated to AI, including those related to bias & fairness. It offers a free responsible AI Diagnostic tool and a PDF version of pwc's Practical Guide to Responsible AI.

Enables developers or auditing entities to discover and test for unwarranted associations between an algorithm's outputs and certain user subpopulations identified by protected features. Produced mainly for Tech teams

Open source tech tool for auditing the data and predictions of machine learning solutions for their fairness. Requires relatively light technology background (can be used by non-developers)

Responsible Innovation is a toolkit for developers that provides a set of practices in development, for anticipating and addressing the potential negative impacts of technology on people. It covers applying Microsoft's AI principles of fairness, and approaches for harms modeling and community jury-style reviews.

Open-source package for training interpretable (explainable) ML models

A library that implements fairness-aware machine learning algorithms. Produced mainly for Tech teams.

Open sourced bias testing tool useful for developers, that seems active for updating. Produced mainly for Tech teams

This extensible open source toolkit can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle. We invite you to use and improve it. Produced mainly for Tech teams