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.

ETSI GR ENI 012 V 1.1.1 - Experiential Networked Intelligence (ENI) - Reactive In-situ Flow Information Telemetry



The present document will describe the motivation, requirements, and challenges of using flow-oriented on-path telemetry techniques which provides relevant measurement or event reports to the AI-enabled network entities. 
The present document will outline a reference framework, named as "In-situ Flow Information Telemetry (IFIT)" and identify technical requirements, including: modes of flow-oriented on-path telemetry; IFIT-based reactive telemetry framework; and technical requirements, including intelligent flow and packet selection, intelligent data export, dynamic network probe, on-demand underlying technique selection. © 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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Tags:

  • System architecture
  • Data processing
  • Interoperability
  • data sharing

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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.