• Content Type

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.

No Results Found

We've not been able to find current content that fits your search criteria.

View All

Forums

Events

Published standards

ANSI/CTA 2090

The Use of Artificial Intelligence in Health Care: Trustworthiness

See more details
Healthcare and medicine - Clinical medicineHealthcare and medicine - Medical devicesAI-specificAccuracy and performance
See more
Artificial Intelligence (AI) is quickly becoming a pervasive tool in the health care industry. This standard identifies the core requirements…
Published
Last Updated: 18 Jul 2024
ETSI GR SAI 004 V 1.1.1

Securing Artificial Intelligence (SAI) – Problem Statement

See more details
HorizontalAI-specificBias and discriminationData collection
See more
This work item describes the challenges of securing AI-based systems and solutions, including challenges relating to data, algorithms and models…
Published
Last Updated: 18 Jul 2024

Standards in development

This guide defines a machine learning framework that allows a computing task to be decomposed and distributed across edge and cloud nodes. This guide provides a blueprint for data usage, model learning, and computing collaboration in edge computing environments while…
Domain:
Horizontal
See more
0 replies
0 followers
Pre-draft
Standards Body: IEEE
Last updated: 12 Jun 2025
This recommended practice provides a framework for the use of large-scale pre-trained deep learning models, including approaches, taxonomies, related roles, and activities, software toolkits, application ability key performance indicators as well as assessment means. © Copyright 2024 IEEE – All…
Domain:
Horizontal
Scope:
AI-specific
See more
0 replies
0 followers
Pre-draft
Standards Body: IEEE
Last updated: 12 Jun 2025
This guide provides data contribution measurement methods for federated machine learning. The document provides guidance with respect to data trading feasibility for federated machine learning. The guide describes three main aspects: 1) Framework for data contribution evaluation of federated machine…
Domain:
Horizontal
Topic:
Data quality
See more
0 replies
0 followers
Pre-draft
Standards Body: IEEE
Last updated: 12 Jun 2025