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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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Published standards

IEEE 7000-2021

IEEE Standard Model Process for Addressing Ethical Concerns during System Design

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HorizontalAI-enabling - Project managementAI-enabling - Risk managementAccountability
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A set of processes by which organizations can include consideration of ethical values throughout the stages of concept exploration and…
Published
Last Updated: 19 Jul 2024
ANSI/CTA 2096

Guidelines for Developing Trustworthy Artificial Intelligence Systems

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HorizontalAI-specificAccountabilityAccuracy and performance
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This recommended practice will describe things developers of artificial intelligence (AI) systems should consider for their systems to be considered…
Published
Last Updated: 18 Jul 2024

Standards in development

This document specifies a method for evaluating the fairness of machine learning. Multiple causes contribute to the unfairness of machine learning. In this document, these causes of machine learning unfairness are categorized. The widely recognized and used definitions of machine…
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Standards Body: IEEE
Last updated: 14 Apr 2025
This standard defines a comprehensive framework for federated machine learning of semantic information agents. It targets two primary layers: • Information Protocol Layer: This layer focuses on binary compression and protocol-level data structures for federated information exchange, with an emphasis…
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Standards Body: IEEE
Last updated: 14 Apr 2025
This standard outlines the toolchain for deploying artificial intelligence (AI) models on edge devices and specifies the functional requirements for this process. The standard covers key areas such as frontend adaptation, model compression, graph optimization, backend adaptation, compiling optimization, and…
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Standards Body: IEEE
Last updated: 14 Apr 2025