Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Intersectional Fairness



Intersectional Fairness

Intersectional bias is a form of discrimination towards groups of people with different, sensitive characteristics (e.g. gender, race, age, sexuality, religion, disability, etc.). While other bias mitigation strategies address bias towards one sensitive characteristics, they often fail to account for the intersection of such variables.

Intersectional Fairness (ISF) is an open source technology developed by Fujitsu that can detect and effectively mitigate such destructive biases. ISF is hosted as an open source project by the Linux Foundation.

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.