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Trustworthy AI

Here are topics relevant to designing, developing and deploying AI systems that are trustworthy. This thematic overview will cover the characteristics of trustworthy AI systems and other governance measures to ensure that AI is built responsibly.

Highlights

Watch the recording of the Introduction to Trustworthy AI from the Hub’s launch event, go the forums to discuss what trustworthy AI means and see ISO’s 2020 standard on trustworthiness in AI systems.

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AI RMF

NIST Artifical Intelligence Risk Management Framework

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HorizontalAI-specificAccountabilityBias and discrimination
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In collaboration with the private and public sectors, NIST has developed a framework to better manage risks to individuals, organizations,…
Published
Last Updated: 18 Jul 2024

Standards in development

This document is a guide and record of the development for the NIST (National Institute of Standards and Technology) glossary of terms for trustworthy and responsible artificial intelligence (AI) and machine learning (ML). The glossary effort seeks to promote a…
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Standards Body: National Institute of Standards and Technology
Last updated: 14 Apr 2025
This document describes the principles and framework for environmental impact measurement of artificial intelligence systems and services and provides guidelines for impact reduction throughout the lifecycle. It includes a framework for defining the environmental impact of artificial intelligence, aharmonized calculation…
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Standards Body: CEN
Last updated: 14 Apr 2025
This recommended practice specifies the general requirements of three dimensional (3D) object reconstruction based on deep learning, including terminology, requirements for data format, functional processes, application scenarios and evaluating, metrics for evaluating the processes and effect of 3D object reconstruction.…
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Standards Body: IEEE
Last updated: 14 Apr 2025