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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IEEE 3129-2023 - Standard for Robustness Testing and Evaluation of Artificial Intelligence (AI)-based Image Recognition Service

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This standard provides test specifications with a set of indicators for interference and adversarial attacks, which can be used to evaluate the robustness of Artificial Intelligence-based Image Recognition services. This standard specifies robustness requirements and establishes an assessment framework to evaluate the robustness of Artificial Intelligence-based Image Recognition service under various settings. ©IEEE 2022. All rights reserved.

The information about this standard has been compiled by the AI Standards Hub, an initiative dedicated to knowledge sharing, capacity building, research, and international collaboration in the field of AI standards. You can find more information and interactive community features related to this standard by visiting the Hub’s AI standards database here. To access the standard directly, please visit the developing organisation’s website.

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  • robustness
  • Security and resilience

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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.