Artificial Intelligence

This CEN Workshop Agreement has been drafted and approved by a Workshop of representatives of interested parties, the constitution of which is indicated in the foreword of this Workshop Agreement. The formal process followed by the Workshop in the development of this Workshop Agreement has been endorsed by the National Members of CEN but neither the National Members of CEN nor the CEN-CENELEC Management Centre can be held accountable for the technical content of this CEN Workshop Agreement or possible conflicts with standards or legislation. This CEN Workshop Agreement can in no way be held as being an official standard developed by CEN and its Members. This CEN Workshop Agreement is publicly available as a reference document from the CEN Members National Standard Bodies.

This document describes the principles and framework for environmental impact measurement of artificial intelligence systems and services and provides guidelines for impact reduction throughout its lifecycle. It includes: - A framework for defining the environmental impact of artificial intelligence - A harmonized calculation method for assessing the environmental impact of artificial intelligence systems and services - Reporting guidelines - Best practices for reducing the environmental impact of AI systems and services throughout their lifecycle. This document is aimed at organizations developing AI systems and services and organizations using AI systems and services, but also at all actors in the value chain who are required to use AI systems and services.

This document specifies the evaluation of computer vision systems, in the sense of measuring the quality of a system’s results to assess its functional suitability. It provides a definition of evaluation methods for those systems, together with guidance on how to select, implement and interpret those evaluation methods. This document covers quantitative metrics as well as other evaluation methods. It includes requirements on the implementation of the described metrics, and further requirements on the technical resources involved in the evaluation process.

This document provides methods and mechanisms to assess the reliability of an AI system. It describes the metrics of reliability and the procedure for reliability assessment from a statistical perspective

This document specifies the requirements and provides guidance for the definition, implementation and maintenance of a quality management system for organizations that provide AI systems. This document is intended to support the organization in meeting applicable regulatory requirements. It is primarily intended for organizations placing on the market or putting into service high-risk AI systems and is not specific to any particular sector.

Artificial Intelligence conformity assessment serves the purpose of providing notice and assurance to stakeholders about conformity against stated requirements. It maps the conformity assessment activities to the different phases of the AI system life cycle. This document provides procedures and processes for conformity assessment activities related to AI systems. The intended audience for this document is primarily conformity assessment scheme developers, owners and operators that evaluate, test, assess and certify AI systems. It is also useful for organizations and people that are not scheme owners or operators, such as AI system stakeholders including AI system developers, providers, customers, partners and regulatory authorities.