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.

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Digital Security

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If you have a tool that you think should be featured in the Catalogue of AI Tools & Metrics, we would love to hear from you!

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This page includes technical metrics and methodologies for measuring and evaluating AI trustworthiness and AI risks. These metrics are often represented through mathematical formulas that assess the technical requirements for achieving trustworthy AI in a particular context. They can help to ensure that a system is fair, accurate, explainable, transparent, robust, safe, or secure.
Objective Digital Security
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Time until Adversary’s Success 15 related use cases

The most general time-based metric measures the time until the adversary’s success. It assumes that the adversary will succeed eventually, and is therefore an example of a pessimistic metric. This metric relies on a definition of success, and varies depend...

Objectives:

PerformanceRobustnessDigital Security

Amount of Leaked Information 15 related use cases

This metric counts the information items S disclosed by a system, e.g., the number of compromised users. However, this metric does not indicate the severity of a leak because it does not account for the
sensitivity of the leaked information.

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Objectives:

Privacy & Data Governance & TraceabilityDigital Security
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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.