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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ETSI GR ENI 007 V 1.1.1 - Experiential Networked Intelligence (ENI) - ENI Definition of Categories for AI Application to Networks

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This Work Item will address the aspects of gradual implementation of networked intelligence and specify a categorization framework for systems based on several different levels (e. g. 5, ranging from fully manual to fully autonomic systems as written in ENI whitepaper). This categorization framework will be based on the amount of network engineer intervention and attentiveness required and the expected interfaces with the assisted system. The details of each level will be defined according to scenarios supported and techniques needed. © Copyright 2023, ETSI

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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Geographical scope:

Tags:

  • Interoperability

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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.