Information technology — Artificial intelligence — Artificial intelligence concepts and terminology

This document establishes terminology for AI and describes concepts in the field of AI. This document can be used in the development of other standards and in support of communications among diverse, interested parties or stakeholders. This document is applicable to all types of organizations (e.g. commercial enterprises, government agencies, not-for-profit organizations).

Technologies de l'information — Intelligence artificielle — Concepts et terminologie relatifs à l'intelligence artificielle

General Information

Status
Published
Publication Date
18-Jul-2022
Current Stage
6060 - International Standard published
Due Date
07-Mar-2022
Completion Date
19-Jul-2022
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INTERNATIONAL ISO/IEC
STANDARD 22989
First edition
2022-07
Information technology — Artificial
intelligence — Artificial intelligence
concepts and terminology
Technologies de l'information — Intelligence artificielle — Concepts
et terminologie relatifs à l'intelligence artificielle
Reference number
ISO/IEC 22989:2022(E)
© ISO/IEC 2022
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ISO/IEC 22989:2022(E)
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© ISO/IEC 2022

All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may

be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on

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Published in Switzerland
© ISO/IEC 2022 – All rights reserved
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ISO/IEC 22989:2022(E)
Contents Page

Foreword ....................................................................................................................................................................................................................................... vi

Introduction .............................................................................................................................................................................................................................vii

1 Scope ................................................................................................................................................................................................................................. 1

2 Normative references ..................................................................................................................................................................................... 1

3 Terms and definitions .................................................................................................................................................................................... 1

3.1 Terms related to AI ............................................................................................................................................................................. 1

3.2 Terms related to data........................................................................................................................................................................ 6

3.3 Terms related to machine learning ...................................................................................................................................... 8

3.4 Terms related to neural networks ..................................................................................................................................... 10

3.5 Terms related to trustworthiness ...................................................................................................................................... 11

3.6 Terms related to natural language processing ....................................................................................................... 13

3.7 Terms related to computer vision ...................................................................................................................................... 16

4 Abbreviated terms ..........................................................................................................................................................................................16

5 AI concepts ..............................................................................................................................................................................................................17

5.1 General ........................................................................................................................................................................................................ 17

5.2 From strong and weak AI to general and narrow AI ......................................................................................... 17

5.3 Agent ............................................................................................................................................................................................................. 17

5.4 Knowledge ............................................................................................................................................................................................... 18

5.5 Cognition and cognitive computing .................................................................................................................................. 19

5.6 Semantic computing ....................................................................................................................................................................... 19

5.7 Soft computing ..................................................................................................................................................................................... 19

5.8 Genetic algorithms ........................................................................................................................................................................... 19

5.9 Symbolic and subsymbolic approaches for AI ......................................................................................................... 19

5.10 Data ................................................................................................................................................................................................................ 20

5.11 Machine learning concepts ....................................................................................................................................................... 21

5.11.1 Supervised machine learning .............................................................................................................................. 21

5.11.2 Unsupervised machine learning ....................................................................................................................... 21

5.11.3 Semi-supervised machine learning ................................................................................................................ 22

5.11.4 Reinforcement learning ............................................................................................................................................22

5.11.5 Transfer learning ............................................................................................................................................................ 22

5.11.6 Training data ........................................................................................................................................... ............................22

5.11.7 Trained model ....................................................................................................................................................................22

5.11.8 Validation and test data ............................................................................................................................................ 22

5.11.9 Retraining ..............................................................................................................................................................................23

5.12 Examples of machine learning algorithms ................................................................................................................. 24

5.12.1 Neural networks .............................................................................................................................................................. 24

5.12.2 Bayesian networks ........................................................................................................................................................ 25

5.12.3 Decision trees ..................................................................................................................................................................... 25

5.12.4 Support vector machine ............................................................................................................................................25

5.13 Autonomy, heteronomy and automation ...................................................................................................................... 26

5.14 Internet of things and cyber-physical systems ....................................................................................................... 27

5.14.1 General ..................................................................................................................................................................................... 27

5.14.2 Internet of things ............................................................................................................................................................ 27

5.14.3 Cyber-physical systems ............................................................................................................................................. 27

5.15 Trustworthiness ................................................................................................................................................................................28

5.15.1 General .....................................................................................................................................................................................28

5.15.2 AI robustness ........................................................................................................................................... ...........................28

5.15.3 AI reliability .........................................................................................................................................................................29

5.15.4 AI resilience ......................................................................................................................................................................... 29

5.15.5 AI controllability .............................................................................................................................................................29

5.15.6 AI explainability ................................... ............................................................................................................................29

5.15.7 AI predictability ...............................................................................................................................................................30

iii
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ISO/IEC 22989:2022(E)

5.15.8 AI transparency ...............................................................................................................................................................30

5.15.9 AI bias and fairness .......................................................................................................................................................30

5.16 AI verification and validation ........................................................................................................................................... ...... 31

5.17 Jurisdictional issues ........................................................................................................................................................................ 31

5.18 Societal impact .................................................................................................................................................................................... 32

5.19 AI stakeholder roles ........................................................................................................................................................................ 32

5.19.1 General ..................................................................................................................................................................................... 32

5.19.2 AI provider ............................................................................................................................................................................ 33

5.19.3 AI producer ........................................................................................................................................................................... 33

5.19.4 AI customer ..........................................................................................................................................................................34

5.19.5 AI partner ..............................................................................................................................................................................34

5.19.6 AI subject ................................................................................................................................................................................34

5.19.7 Relevant authorities ..................................................................................................................................................... 35

6 AI system life cycle ..........................................................................................................................................................................................35

6.1 AI system life cycle model ......................................................................................................................................................... 35

6.2 AI system life cycle stages and processes ................................................................................................................... 37

6.2.1 General ..................................................................................................................................................................................... 37

6.2.2 Inception ................................................................................................................................................................................. 37

6.2.3 Design and development ..........................................................................................................................................38

6.2.4 Verification and Validation ..................................................................................................................................... 39

6.2.5 Deployment .......................................................................................................................................................................... 39

6.2.6 Operation and monitoring ...................................................................................................................................... 39

6.2.7 Continuous validation .................................................................................................................................................40

6.2.8 Re-evaluation .....................................................................................................................................................................40

6.2.9 Retirement ............................................................................................................................................................................40

7 AI system functional overview ..........................................................................................................................................................40

7.1 General ........................................................................................................................................................................................................40

7.2 Data and information ........................................................................................................................................... .......................... 41

7.3 Knowledge and learning ............................................................................................................................................................. 41

7.4 From predictions to actions ......... ............................................................................................................................................ 42

7.4.1 General ..................................................................................................................................................................................... 42

7.4.2 Prediction .............................................................................................................................................................................. 42

7.4.3 Decision ................................................................................................................................................................................... 43

7.4.4 Action ........................................................................................................................................................................................ 43

8 AI ecosystem ..........................................................................................................................................................................................................43

8.1 General ........................................................................................................................................................................................................ 43

8.2 AI systems................................................................................................................................................................................................ 45

8.3 AI function ............................................................................................................................................................................................... 45

8.4 Machine learning ............................................................................................................................................................................... 45

8.4.1 General ..................................................................................................................................................................................... 45

8.5 Engineering ............................................................................................................................................................................................46

8.5.1 General .....................................................................................................................................................................................46

8.5.2 Expert systems .................................................................................................................................................................46

8.5.3 Logic programming ......................................................................................................................................................46

8.6 Big data and data sources — cloud and edge computing ..............................................................................46

8.6.1 Big data and data sources........................................................................................................................................46

8.6.2 Cloud and edge computing .....................................................................................................................................48

8.7 Resource pools .....................................................................................................................................................................................50

8.7.1 General .....................................................................................................................................................................................50

8.7.2 Application-specific integrated circuit ........................................................................................................50

9 Fields of AI................................................................................................................................................................................................................51

9.1 Computer vision and image recognition....................................................................................................................... 51

9.2 Natural language processing .................................................................................................................................................. 51

9.2.1 General ..................................................................................................................................................................................... 51

9.2.2 Natural language processing components ............................................................................................... 52

9.3 Data mining ............................................................................................................................................................................................54

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ISO/IEC 22989:2022(E)

9.4 Planning .....................................................................................................................................................................................................54

10 Applications of AI systems ......................................................................................................................................................................54

10.1 General ........................................................................................................................................................................................................54

10.2 Fraud detection ................................................................................................................................................................................... 55

10.3 Automated vehicles .........................................................................................................................................................................55

10.4 Predictive maintenance...............................................................................................................................................................56

Annex A (informative) Mapping of the AI system life cycle with the OECD’s definition of an

AI system life cycle ..........................................................................................................................................................................................57

Bibliography .............................................................................................................................................................................................................................59

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ISO/IEC 22989:2022(E)
Foreword

ISO (the International Organization for Standardization) and IEC (the International Electrotechnical

Commission) form the specialized system for worldwide standardization. National bodies that are

members of ISO or IEC participate in the development of International Standards through technical

committees established by the respective organization to deal with particular fields of technical

activity. ISO and IEC technical committees collaborate in fields of mutual interest. Other international

organizations, governmental and non-governmental, in liaison with ISO and IEC, also take part in the

work.

The procedures used to develop this document and those intended for its further maintenance are

described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for

the different types of document should be noted. This document was drafted in accordance with the

editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives or www.iec.ch/members_

experts/refdocs).

Attention is drawn to the possibility that some of the elements of this document may be the subject

of patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent

rights. Details of any patent rights identified during the development of the document will be in the

Introduction and/or on the ISO list of patent declarations received (see www.iso.org/patents) or the IEC

list of patent declarations received (see patents.iec.ch).

Any trade name used in this document is information given for the convenience of users and does not

constitute an endorsement.

For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and

expressions related to conformity assessment, as well as information about ISO's adherence to the

World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see www.iso.org/

iso/foreword.html. In the IEC, see www.iec.ch/understanding-standards.

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 and www.iec.ch/national-

committees.
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ISO/IEC 22989:2022(E)
Introduction

Advancements in computing capacity, reduction of costs of computation, availability of large amounts

of data from many sources, inexpensive online learning curricula and algorithms capable of meeting or

exceeding human level performance in particular tasks for speed and accuracy have enabled practical

applications of AI, making it an increasingly important branch of information technology.

AI is a highly interdisciplinary field broadly based on computer science, data science, natural sciences,

humanities, mathematics, social sciences and others. Terms such as “intelligent”, “intelligence”,

“understanding”, “knowledge”, “learning”, “decisions”, “skills”, etc. are used throughout this document.

However, it is not the intention to anthropomorphize AI systems, but to describe the fact that some AI

systems can rudimentarily simulate such characteristics.

There are many areas of AI technology. These areas are intricately linked and developing rapidly so it is

difficult to fit the relevance of all technical fields into a single map. Research of AI includes aspects such

as aspects including “learning, recognition and prediction”, “inference, knowledge and language” and

[23]

“discovery, search and creation”. Research also addresses interdependencies among these aspects .

The concept of AI as an input and output process flow is shared by many AI researchers, and research on

each step of this process is ongoing. Standardized concepts and terminology are needed by stakeholders

of the technology to be better understood and adopted by a broader audience. Furthermore, concepts

and categories of AI allow for a comparison and classification of different solutions with respect

to properties like trustworthiness, robustness, resilience, reliability, accuracy, safety, security and

privacy. This enables stakeholders to select appropriate solutions for their applications and to compare

the quality of available solutions on the market.

As this document does provide a definition for the term AI in the sense of a discipline only, the context

for its usage can be described as follows: AI is a technical and scientific field devoted to the engineered

system that generates outputs such as content, forecasts, recommendations or decisions for a given set

of human-defined objectives.

This document provides standardized concepts and terminology to help AI technology to be better

understood and used by a broader set of stakeholders. It is intended for a wide audience including

experts and non-practitioners. The reading of some specific clauses can however be easier with a

stronger background in computer science. These concerns are described primarily Clauses 5.10, 5.11

and 8, which are more technical than the rest of the document.
vii
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INTERNATIONAL STANDARD ISO/IEC 22989:2022(E)
Information technology — Artificial intelligence —
Artificial intelligence concepts and terminology
1 Scope

This document establishes terminology for AI and describes concepts in the field of AI.

This document can be used in the development of other standards and in support of communications

among diverse, interested parties or stakeholders.

This document is applicable to all types of organizations (e.g. commercial enterprises, government

agencies, not-for-profit organizations).
2 Normative references
There are no normative references in this document.
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.

ISO and IEC maintain terminology databases for use in standardization at the follow

...

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