Recommendation ITU-T Y.3183 provides a framework for machine learning-assisted network slicing management, leveraging vertical end users’ feedback on quality of…
AI-specific
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ITU-T H.862.6
Functional requirements for counselling services based on artificial emotional intelligence
VDI/VDE 3550 Blatt 1
Computational Intelligence – Artificial neuronal network in automation – Terms and definitions
The document specifies for industrial users of neuronal networks a uniform basis for using the most important terms and definitons.…
ANSI/CTA 2116
CTA Artificial Intelligence in Health Care-Practices for Identifying and Managing Bias
This voluntary standard identifies types of bias, sources of bias, and bias management practices for health care applications of Artificial…
ISO/IEC DIS 24392
Cybersecurity — Security reference model for industrial Internet platform (SRM- IIP)
This document presents specific characteristics of IIPs, including related security threats, context-specific security control objectives and security controls.This document covers…
ITU-T L Suppl. 48 (07/2022)
Data centre energy saving: Application of artificial intelligence technology in improving energy efficiency of telecommunication room and data centre infrastructure
Telecommunication room and data centre (DC) infrastructure includes a large number of items of information and communication equipment. In order…
VDE-AR-E 2842-61-4
Development and trustworthiness of autonomous/cognitive systems – Part 61-4: Development at System Level; Text in English
Reference model for trustworthy Artificial intelligence (AI) has the great potential to change society, the economy and the coexistence of…
BS 9347:2024
Facial recognition technology. Ethical use and deployment in video surveillance-based systems. Code of practice
Compared with the traditional network, Recommendation ITU-T Y.3656 can provide better integration and more intelligent capabilities, such as the capabilities…
ITU-T Y.3181 (09/2022)
Architectural framework for machine learning sandbox in future networks including IMT-2020
Recommendation ITU-T Y.3181 provides an architectural framework for machine learning (ML) sandbox in future networks including IMT-2020. More precisely, it…
DIN SPEC 92001-3
Artificial Intelligence – Life Cycle Processes and Quality Requirements – Part 3: Explainability; Text in English
This document provides a domain-independent guide to appropriate approaches and methods to promote explainability throughout all stages of an AI…
