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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 this standard about? This document is the reference framework for the Big Picture project. The Big Picture aims at monitoring the consistency of published standards and current or future standardization projects. The Big Picture enables the standardization stakeholders…
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Standards Body: ISO
Last updated: 7 Jan 2025
What is PAS 1881:2022 about? PAS 1881:2022 is the first full revision of PAS 1881:2020 to reflect learning from recent automated vehicle trials and input from stakeholders. It deals with how to build operational safety cases for trialling and testing…
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Standards Body: BSI
Last updated: 7 Jan 2025
New broadcasting technologies driven by artificial intelligence (AI) are being introduced to the broadcasting workflow. These technologies are intended to increase productivity, efficiency and creative opportunities during programme production, and to convey information to viewers quickly, accurately and automatically. This…
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Standards Body: ITU
Last updated: 7 Jan 2025
This document reviews current aerospace software, hardware, and system development standards used in the certification/approval process of safety-critical airborne and ground-based systems, and assesses whether these standards are compatible with a typical Artificial Intelligence (AI) and Machine Learning (ML) development…
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Standards Body: SAE
Last updated: 7 Jan 2025
Data interchange and standard software services for test and diagnostic environments are defined by Artificial Intelligence Exchange and Service Tie to All Test Environments (AIESTATE). The purpose of AI-ESTATE is to standardize interfaces for functional elements of an intelligent diagnostic…
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Standards Body: IEC, BSI
Last updated: 7 Jan 2025
This document provides background about existing methods to assess theĀ robustnessĀ ofĀ neural networks. Ā© ISO/IEC 2022 All rights reserved
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This document provides guidelines for evaluation of AI systems using an AI system quality model. The document is applicable to all types of organizations engaged in the development and the use of artificial intelligence. PurposeAI systems can be very challenging…
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This DIN SPEC has been developed within a DIN SPEC consortium. The document was developed and approved by organizations named in the Foreword. This document specifies general guidance and requirements for the development and use of methods for quantifying uncertainty…
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Standards Body: DIN
Last updated: 7 Jan 2025
This document discusses the concept of task in the case of AI applied to natural language, and proposes a landscaping of the AI tasks related to the analysis or generation of natural language, as well as other language-related functionalities that…
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This document provides a domain-independent guide to appropriate approaches and methods to promote explainability throughout all stages of an AI model’s life cycle. A better understanding of explainable AI helps organizations embed principles of trust and transparency into their AI-based…
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Standards Body: DIN
Last updated: 7 Jan 2025
This document provides a data quality governance framework for analytics and machine learning to enable governing bodies of organizations to direct and oversee the implementation and operation of data quality measures, management, and related processes with adequate controls throughout the…
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