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Standards Database

Find information on AI-related standards using the search and filtering capabilities below. This database currently covers nearly 300 relevant standards that are being developed or have been published by a range of prominent Standards Development Organisations.

Hover over the filter categories here to learn more about them:

Domain The industry or sector that the standard covers (e.g. Energy).

Type of standard Whether the standard covers terminology, processes, performance requirements or measurement requirements.
Application The type of technology, method or application covered by the standard. (E.g. Natural language processing)

Stage of development If the standards is pre-draft, draft or published.
Scope Whether the standard is focused entirely on AI, or is adjacent to AI.

Issuing body The standards body or organisation that issued the standard.
Topic The theme, principle or area covered by the standard (e.g. bias and discrimination).

Committee The standards committee that developed this standard.
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This DIN SPEC in accordance with the PAS procedure has been drawn up by a DIN SPEC (PAS)-consortium set up on a temporary basis. This DIN SPEC (PAS) has been developed and approved by the authors named in the foreword.…
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Standards Body: DIN
Last updated: 7 Jan 2025
This document is intended for organizations that have formalized, or wish to formalize, their approach to ethics. AFNOR Copyright Ā© 2018, All rights reserved
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Last updated: 7 Jan 2025
This Guide for Verification of Autonomous Systems enables the user to define a customized process for verification of their autonomous system based on their available resources. It documents best practices across all levels of abstraction within a given system. It…
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Standards Body: IEEE
Last updated: 7 Jan 2025
This guide specifies an architectural framework that facilitates the adoption of explainable artificial intelligence (XAI). This guide defines an architectural framework and application guidelines for XAI, including: 1) description and definition of explainable AI, 2) the categorizes of explainable AI…
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Standards Body: IEEE
Last updated: 7 Jan 2025
Recommendation ITU-T P.1402 introduces machine-learning techniques and their application for quality of service (QoS) and quality of experience (QoE) prediction and network performance management in telecommunication scenarios. Especially, the design of training and evaluation data is described and means to…
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Standards Body: ITU
Last updated: 7 Jan 2025
The proposed document will establish a framework for quantification of environmental impact of AI and its long-term sustainability, and encourage AI developers and users to improve efficiency of AI use. It will also provide a summary of the state of…
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Standards Body: CEN
Last updated: 7 Jan 2025
What is BS ISO 37000:2021 about? Governance helps organizations achieve their purpose in an effective and responsible way and meet rising societal expectations around accountability, fairness and ethics. BS ISO 37000:2021 supplies authoritative and comprehensive guidance on what governance is…
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Standards Body: ISO, BSI
Last updated: 7 Jan 2025
OverviewVisit the preview section for more information. Copyright Ā© IEC 2023. All rights reserved.
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Standards Body: IEC
Last updated: 7 Jan 2025
This Recommendation specifies a functional framework for network service provisioning based on artificial intelligence (AI) in future networks, including international mobile telecommunication-2020 (IMT-2020). This Recommendation addresses the following aspects: – a business role-based model for AI-based network service provisioning; –…
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Standards Body: ITU
Last updated: 7 Jan 2025
Recommendation ITU-T Y.4471 defines a reference functional architecture of network-based driving assistance (NDA) for autonomous vehicles. It clarifies the concept of NDA, specifies key functional entities and defines reference points between entities. The use cases and operational procedures are also…
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Standards Body: ITU
Last updated: 7 Jan 2025
This Recommendation specifies a functional architecture of quality of service (QoS) assurance based on machine learning (ML) for the international mobile telecommunications-2020 (IMT-2020) network. This Recommendation includes: – an overview of the architectural framework for ML in the IMT-2020 network…
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Standards Body: ITU
Last updated: 7 Jan 2025
Recommendation ITU-T Y.3156 describes the requirements and functional roles of AI-assisted analysis in support of the lifecycle management and orchestration of network slicing. It is intended to be used for the future enhanced operation and maintenance management of network slicing…
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Standards Body: ITU
Last updated: 7 Jan 2025