System quality Archives - AI Standards Hub

Recommendation ITU-T Y.3183 provides a framework for machine learning-assisted network slicing management, leveraging vertical end users’ feedback on quality of…

Published

Last Updated: 31 Oct 2024

VDE-AR-E 2842-61-4

Development and trustworthiness of autonomous/cognitive systems – Part 61-4: Development at System Level; Text in English

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Horizontal AI-specific Organisational governance Project management

System lifecycle System quality Process, management and governance

Reference model for trustworthy Artificial intelligence (AI) has the great potential to change society, the economy and the coexistence of…

Published

Last Updated: 13 Jun 2025

DIN SPEC 92001-3

Artificial Intelligence – Life Cycle Processes and Quality Requirements – Part 3: Explainability; Text in English

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Horizontal AI-specific Explainability and transparency System quality

Product and performance requirements

This document provides a domain-independent guide to appropriate approaches and methods to promote explainability throughout all stages of an AI…

Published

Last Updated: 31 Oct 2024

Content Type

Software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Quality models for AI systems

Quality requirements for video-based methods of personnel selection

Human guarantee of systems founded on artificial intelligence in healthcare

Artificial intelligence — Testing of AI — Part 2: Overview of testing AI systems

Systems and software engineering. Systems and software quality requirements and evaluation (SQuaRE). Product quality model

Systems and software engineering – Systems and software Quality Requirements and Evaluation (SQuaRE) – Guidance for quality evaluation of artificial intelligence (AI) systems

Implementation and operation of big data applications in the manufacturing industry – Online application of data-driven models

Implementation and operation of big data applications in the manufacturing industry – Validation of models

Development and trustworthiness of autonomous/cognitive systems – Part 61-5: Development at Technology Level; Text in English

Framework for network slicing management assisted by machine learning leveraging quality of experience feedback from verticals

Development and trustworthiness of autonomous/cognitive systems – Part 61-4: Development at System Level; Text in English

Artificial Intelligence – Life Cycle Processes and Quality Requirements – Part 3: Explainability; Text in English

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