National foreword

This Published Document is the UK implementation of ISO/IEC TR 24028:2020.

The UK participation in its preparation was entrusted to Technical Committee ART/1, Artificial Intelligence.

A list of organizations represented on this committee can be obtained on request to its secretary.

This publication does not purport to include all the necessary provisions of a contract. Users are responsible for its correct application.

Compliance with a British Standard cannot confer immunity from legal obligations.

This Published Document was published under the authority of the Standards Policy and Strategy Committee on 30 June 2020.

Foreword

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

Any feedback or questions on this document should be directed to the user’s national standards body. A complete listing of these bodies can be found at www.iso.org/members.html.

Introduction

The goal of this document is to analyse the factors that can impact the trustworthiness of systems providing or using AI, called hereafter artificial intelligence (AI) systems. The document briefly surveys the existing approaches that can support or improve trustworthiness in technical systems and discusses their potential application to AI systems. The document discusses possible approaches to mitigating AI system vulnerabilities that relate to trustworthiness. The document also discusses approaches to improving the trustworthiness of AI systems.

1 Scope

This document surveys topics related to trustworthiness in AIsystems, including the following:

approaches to establish trust in AIsystems through transparency, explainability, controllability, etc.;
engineering pitfalls and typical associated threats and risks to AIsystems, along with possible mitigation techniques and methods; and
approaches to assess and achieve availability, resiliency, reliability, accuracy, safety, security and privacy of AIsystems.

The specification of levels of trustworthiness for AIsystems is out of the scope of this document.

2 Normative references

3 Terms and definitions

4 Overview

5 Existing frameworks applicable to trustworthiness

5.1 Background

5.2 Recognition of layers of trust

5.3 Application of software and data quality standards

5.4 Application of risk management

5.5 Hardware-assisted approaches

6 Stakeholders

6.1 General concepts

6.2 Types

6.3 Assets

6.4 Values

7 Recognition of high-level concerns

7.1 Responsibility, accountability and governance

7.2 Safety

8 Vulnerabilities, threats and challenges

8.1 General

8.2 AI specific security threats

8.3 AI specific privacy threats

8.4 Bias

8.5 Unpredictability

8.6 Opaqueness

8.7 Challenges related to the specification of AI systems

8.8 Challenges related to the implementation of AI systems

8.9 Challenges related to the use of AI systems

8.10 System hardware faults

9 Mitigation measures

9.1 General

9.2 Transparency

9.3 Explainability

9.4 Controllability

9.5 Strategies for reducing bias

9.6 Privacy

9.7 Reliability, resilience and robustness

9.8 Mitigating system hardware faults

9.9 Functional safety

9.10 Testing and evaluation

9.11 Use and applicability

10 Conclusions

Bibliography

PD ISO/IEC TR 24028:2020

Information technology. Artificial intelligence. Overview of trustworthiness in artificial intelligence

Current

Published:

31 Oct 2022