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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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What is a BSI Flex? BSI Flex is a new model of standards development that uses an agile, iterative approach and open consultation to develop consensus-based good practice in areas that change and develop quickly. BSI Flex 236: v1.0 2022-01…
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Standards Body: BSI
Last updated: 7 Jan 2025
This Recommendation describes the functional entities and architecture for emotion enabled multimodal user interface based on artificial neural networks. In particular, the scope of this Recommendation includes: – Architectural framework; – Functional entities; – Interfaces; – Application to multimodal emotion…
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Standards Body: ITU
Last updated: 7 Jan 2025
Recommendation ITU-T L.1040 establishes guidelines and requirements for information and communication technology original equipment manufacturer vendors providing equipment to autonomous vehicles aiming to reduce the amount of future e-waste. Recommendation ITU-T L.1040 analyses the e-waste risks and other sustainability indicators…
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Standards Body: ITU
Last updated: 7 Jan 2025
This VDE application guide “Development and Trustworthiness of autonomous / cognitive Systems – Part 6: After Release of the Solution” specifies a general framework for the development of trustworthy solutions and trustworthy autonomous / cognitive systems, including the requirements for…
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This is part 5 of the VDE-AR-E 2842-61 series of application guides (AR). It describes the requirements for the reference lifecycle phase “Development at Technology Level”. The purpose of the technology level is to provide the approach to develop an…
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Reference model for trustworthy Artificial intelligence (AI) has the great potential to change society, the economy and the coexistence of people in the long term. It can help to reduce emissions, detect diseases, transport people or goods or make processes…
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This VDE application guide, Development and Trustworthiness of autonomous/cognitive Systems – Part 3: Development at Solution Level (whole application) describes the requirements for the management in order to ensure and support a structured approach to the development of an trustworthy…
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This VDE application guide “Development and Trustworthiness of autonomous / cognitive Systems – Part 2: Management”describes the requirements for the management in order to ensure and support a structured approach to the development of an trustworthy autonomous cognitive system. This…
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VDE-AR-E 2842-61-1 specifies a general framework for the development of trustworthy solutions and trustworthy autonomous / cognitive systems, including the requirements for the subsequent phases of Product life cycle (e.g. production, marketing & sales, operation & maintenance, retirement & repair).…
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This standard defines terms related to artificial intelligence and associated technologies in health care including assistive intelligence, synthetic data, remote patient monitoring, and artificial intelligence enabled diagnostic system. This file also includes a copy of CTA-2089. Ā© 2022 American National…
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Standards Body: ANSI
Last updated: 7 Jan 2025
A deep learning software framework provides an easy and fast way for manufactures to develop their own artificial intelligence (AI) applications. However, different frameworks show different performances under different scenarios. Recommendation ITU-T F.748.12 helps to evaluate deep learning software frameworks…
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Standards Body: ITU
Last updated: 7 Jan 2025
Today, companies must evolve their products and services, which creates a pool of new projects in a context of increasing cost and time constraints. Under these conditions, project management has a major role to play, based on the contributions of…
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Last updated: 7 Jan 2025
This document defines terms relating to data quality used in the ISO 8000 series of parts. Ā© BSI 2022 All rights reserved
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Standards Body: ISO, BSI
Last updated: 7 Jan 2025
Digital data deliver value by enhancing all aspects of organizational performance including: — operational effectiveness and efficiency; — safety; — reputation with customers and the wider public; — compliance with statutory regulations; — innovation; — consumer costs, revenues and stock…
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Standards Body: ISO, BSI
Last updated: 7 Jan 2025