ISO/IEC 5338:2023 情報技術 | ページ 2

Foreword

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This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology, Subcommittee SC 42, Artificial intelligence.

Introduction

Artificial intelligence (AI) systems in the fields of computer vision and image recognition, natural language processing, fraud detection, automated vehicles, predictive maintenance and planning have achieved remarkable successes. To build and maintain an AI system, it is an efficient approach to extend the life cycle processes for a traditional software system to include AI-specific life cycle characteristics.

An example of such a specific characteristic of an AI system life cycle is where a system employs machine learning (ML) using training data and it becomes necessary to retrain the ML model using new training data that is more representative of current production data.

ISO/IEC/IEEE 12207 describes software life cycle processes and ISO/IEC/IEEE 15288 describes system life cycle processes. While these life cycle processes are broadly applicable to AI systems, they require the introduction of new processes and the modification of existing processes to accommodate the characteristics of AI systems. This document extends the current generic life cycle process International Standards to make them applicable for AI systems so that the AI system life cycle can benefit from established models and existing practices. Some AI systems are in use in areas which are related to safety, such as health care or traffic control. Such safety critical AI systems need special attention and considerations as described in ISO/IEC TR 5469 ^[5].

Integrating the AI system life cycle into existing processes delivers efficiency gains, better adoption of AI and mutual understanding among AI system stakeholders as defined in ISO/IEC 22989. Such an integrated life cycle approach embraces the fact that AI systems typically are a combination of AI-specific elements and traditional elements such as source code and databases.

This document provides further details on AI system life cycle processes as discussed in ISO/IEC 42001 ^[18].

1 Scope

This document defines a set of processes and associated concepts for describing the life cycle of AI systems based on machine learning and heuristic systems. It is based on ISO/IEC/IEEE 15288 and ISO/IEC/IEEE 12207 with modifications and additions of AI-specific processes from ISO/IEC 22989 and ISO/IEC 23053.

This document provides processes that support the definition, control, management, execution and improvement of the AI system in its life cycle stages. These processes can also be used within an organization or a project when developing or acquiring AI systems. When an element of an AI system is traditional software or a traditional system, the software life cycle processes in ISO/IEC/IEEE 12207 and the system life cycle processes in ISO/IEC/IEEE 15288 can be used to implement that element.

2 Normative references

The following documents are referred to in the text in such a way that some or all of their content constitutes requirements of this document. For dated references, only the edition cited applies. For undated references, the latest edition of the referenced document (including any amendments) applies.

3 Terms and definitions

For the purposes of this document, the terms and definitions given in ISO/IEC 22989, ISO/IEC 23053, ISO/IEC/IEEE 15288, ISO/IEC/IEEE 12207 and the following apply.

ISO and IEC maintain terminology databases for use in standardization at the following addresses:

Bibliography