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AI FAIRNESS 
GLOBAL LIBRARY

Tools, guides, resources, metrics,

and methodologies to support institutions

transforming AI fairness principles into practice. 

All Resources

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TOOLBOX: Dynamics of AI Principles

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English

Guide or manual

AI Ethics Lab

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

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Empowering AI Leadership – An Oversight Toolkit for Boards of Directors

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English & Spanish

Guide

World Economic Forum

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

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Responsible AI

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North America

English

Guide

PwC

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.

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FairTest

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North America

English

Tech tool

Universidad de Columbia, Stanford, EPFL, Saarland Univ., Cornell Tech, Jacobs Institute

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

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Bias and Fairness Audit Toolkit

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North America

English

Tech tool

Chicago University

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)

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Responsible Innovation: A Best Practices Toolkit

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English

Tech tool

Microsoft

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.

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InterpretML

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English

Tech tool

Microsoft

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

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Themis™ o Themis-ML

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North America

English

Tech tool

Massachusetts University

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

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Audit-AI

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North America

English

Tech tool

Pymetrics

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

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AI Fairness 360

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North America

English

Tech tool

IBM

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

Do you want to contribute?

 This is a live Global Library.

This publication was last updated in August 2022. If you have any resource on AI fairness that has not been published on this  Global Library and you would like for it to be considered, or if you are the creator of a resource published here, and would like to edit the information, please send us an email to info@cminds.co

Disclosures:

The material included in this site is not necessarily endorsed by the World Economic Forum, the Global Future Council on AI for Humanity, C Minds and/or other collaborators.

The readers and/or users of each resource must evaluate each tool for his/her specific intended purpose. This first interation includes only free and publicly available resources.

The intelectual property of all of the resources are owned by the creators of each individual resource.

This material may be shared, provided that it is clearly attributed to its creators. This material may not be used for commercial purposes.

Global Future Council on AI for Humanity,WEF with the support of C Minds

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