ISO/IEC FDIS 12792
(Main)Information technology — Artificial intelligence — Transparency taxonomy of AI systems
Information technology — Artificial intelligence — Transparency taxonomy of AI systems
This document defines a taxonomy of information elements to assist AI stakeholders with identifying and addressing the needs for transparency of AI systems. The document describes the semantics of the information elements and their relevance to the various objectives of different AI stakeholders. This document uses a horizontal approach and is applicable to any kind of organization and application involving AI. V02/
Technologies de l'information — Intelligence artificielle — Taxonomie pour la transparence des systèmes d’IA
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International
Standard
ISO/IEC FDIS
ISO/IEC JTC 1/SC 42
Information technology — Artificial
Secretariat: ANSI
intelligence — Transparency
Voting begins on:
taxonomy of AI systems
2025-06-02
Technologies de l'information — Intelligence artificielle —
Voting terminates on:
Taxonomie pour la transparence des systèmes d’IA
2025-07-28
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Reference number
FINAL DRAFT
International
Standard
ISO/IEC FDIS
ISO/IEC JTC 1/SC 42
Information technology — Artificial
Secretariat: ANSI
intelligence — Transparency
Voting begins on:
taxonomy of AI systems
Technologies de l'information — Intelligence artificielle —
Voting terminates on:
Taxonomie pour la transparence des systèmes d’IA
RECIPIENTS OF THIS DRAFT ARE INVITED TO SUBMIT,
WITH THEIR COMMENTS, NOTIFICATION OF ANY
RELEVANT PATENT RIGHTS OF WHICH THEY ARE AWARE
AND TO PROVIDE SUPPOR TING DOCUMENTATION.
© ISO/IEC 2025
IN ADDITION TO THEIR EVALUATION AS
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
BEING ACCEPTABLE FOR INDUSTRIAL, TECHNO
ISO/CEN PARALLEL PROCESSING
LOGICAL, COMMERCIAL AND USER PURPOSES, DRAFT
be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on
INTERNATIONAL STANDARDS MAY ON OCCASION HAVE
the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below
TO BE CONSIDERED IN THE LIGHT OF THEIR POTENTIAL
or ISO’s member body in the country of the requester.
TO BECOME STAN DARDS TO WHICH REFERENCE MAY BE
MADE IN NATIONAL REGULATIONS.
ISO copyright office
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Published in Switzerland Reference number
© ISO/IEC 2025 – All rights reserved
ii
Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms. 4
5 Overview . 4
5.1 General .4
5.2 Organization and usage of the taxonomy .4
5.3 Constraints on transparency disclosures .5
5.4 Concept of transparency .6
6 Stakeholders’ needs and transparency objectives . 7
6.1 General .7
6.2 Transparency objectives and goals .8
6.3 Selected stakeholder roles in transparency .9
7 Context-level taxonomy .11
7.1 General .11
7.2 Societal context .11
7.2.1 General .11
7.2.2 Labour practices .14
7.2.3 Consumer needs . 15
7.3 Environmental context .16
7.3.1 General .16
7.3.2 Particular environmental disclosures .17
7.3.3 Organizational disclosures .18
8 System-level taxonomy . 19
8.1 General .19
8.2 Basic information .19
8.3 Organizational processes . 20
8.3.1 General . 20
8.3.2 Governance . 20
8.3.3 Management system .21
8.3.4 Risk management .21
8.3.5 Quality management .21
8.4 Applicability .21
8.4.1 General .21
8.4.2 Intended purposes . 22
8.4.3 Capabilities . 22
8.4.4 Functional limitations . 22
8.4.5 Recommended uses . 22
8.4.6 Precluded uses . 22
8.5 Overview of technical characteristics . 22
8.5.1 General . 22
8.5.2 Expected inputs and outputs . 23
8.5.3 Production data . 23
8.5.4 Logging and storing . 23
8.5.5 System decomposition . 23
8.5.6 Application programming interface .24
8.5.7 Human factors .24
8.5.8 Deployment methods .24
8.5.9 Configuration management .24
8.6 Access to internal elements . 25
© ISO/IEC 2025 – All rights reserved
iii
8.7 Quality and performance . 26
8.7.1 General . 26
8.7.2 Verification and validation processes . 26
8.7.3 Runtime measurements . 26
8.7.4 Comparison with alternative systems .27
9 Model-level taxonomy .27
9.1 General .27
9.2 Basic information .27
9.3 Usage and model interplay . .
...
ISO/IEC DISFDIS 12792:2024(en)
ISO/IEC JTC 1/SC 42
Secretariat: ANSI
Date: 2024-07-022025-05-19
Information technology — Artificial intelligence — Transparency
taxonomy of AI systems
Technologies de l'information — Intelligence artificielle — Taxonomie pour la transparence des systèmes d’IA
FDIS stage
MUST BE USED
FOR FINAL
ISO/IEC DISFDIS 12792:20242025(en)
© ISO/IEC 20242025
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 the internet or an intranet, without prior written permission. Permission can be requested from either ISO
at the address below or ISO’s member body in the country of the requester.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: + 41 22 749 01 11
E-mail: copyright@iso.org
Website: www.iso.org
Published in Switzerland
© ISO/IEC 20242025 – All rights reserved
ii
ISO/IEC DISFDIS 12792:20242025(en)
Contents
Foreword . v
Introduction . vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms . 4
5 Overview . 4
5.1 General. 4
5.2 Organization and usage of the taxonomy . 4
5.3 Constraints on transparency disclosures . 6
5.4 Concept of transparency . 7
6 Stakeholders’ needs and transparency objectives . 9
6.1 General. 9
6.2 Transparency objectives and goals . 10
6.3 Selected stakeholder roles in transparency . 10
7 Context-level taxonomy . 13
7.1 General. 13
7.2 Societal context . 13
7.3 Environmental context . 19
8 System-level taxonomy . 22
8.1 General. 22
8.2 Basic information. 22
8.3 Organizational processes . 23
8.4 Applicability . 24
8.5 Overview of technical characteristics . 26
8.6 Access to internal elements . 28
8.7 Quality and performance . 29
9 Model-level taxonomy . 30
9.1 General. 30
9.2 Basic information. 31
9.3 Usage and model interplay . 31
9.4 Technical characteristics . 32
9.5 Data used . 35
9.6 Functional correctness . 36
10 Dataset-level taxonomy . 37
10.1 General. 37
10.2 Basic information. 37
10.3 Data provenance . 38
10.4 Data properties . 40
10.5 Dataset domain and purposes . 41
10.6 Data biases and limitations . 42
10.7 Societal considerations . 42
10.8 Data preparation performed . 43
MUST BE USED
10.9 Dataset maintenance . 44
Annex A (informative) Examples of transparency templates . 45
FOR FINAL
Annex B (informative) Examples of stakeholder roles in transparency . 46
© ISO/IEC 20242025 – All rights reserved
iii
ISO/IEC DISFDIS 12792:20242025(en)
Bibliography . 48
© ISO/IEC 20242025 – All rights reserved
iv
ISO/IEC DISFDIS 12792:20242025(en)
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).
ISO and IEC draw attention to the possibility that the implementation of this document may involve the use of
(a) patent(s). ISO and IEC take no position concerning the evidence, validity or applicability of any claimed
patent rights in respect thereof. As of the date of publication of this document, ISO and IEC had not received
notice of (a) patent(s) which may be required to implement this document. However, implementers are
cautioned that this may not represent the latest information, which may be obtained from the patent database
available at www.iso.org/patents and https://patents.iec.ch. ISO and IEC shall not be held responsible for
identifying any or all such patent rights.
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., in collaboration with the European Committee for Standardization
(CEN) Technical Committee CEN/CLC/JTC 21, Artificial Intelligence, in accordance with the Agreement on
technical cooperation between ISO and CEN (Vienna Agreement).
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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MUST BE USED
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© ISO/IEC 20242025 – All rights reserved
v
ISO/IEC DISFDIS 12792:20242025(en)
Introduction
The objectives of this document include:
— — improving trustworthiness, accountability and communication among different AI stakeholders,
including partners in a supply chain, customers, users, society and regulators, by establishing a consistent
terminology around transparency of AI systems;
— — providing AI stakeholders with information about different elements of transparency with their
relevance and possible limitations to different use cases and target audience;
— — serving as a basis for developing technology-specific, industry-specific or region-specific standards for
transparency of AI systems.
Transparency for AI systems is the property of a system that stakeholders receive relevant information about
the system. This can include information on items such as system features, limitations, data, system design
and design choices (see ISO/IEC 22989:2022, 5.15.8).
Transparency enables relevant stakeholders to have access to information, so they can better understand how
an AI system is developed, deployed and can be used. For example, this allows an AI customer (such as an AI
user) of an AI system to determine if it is appropriate for their situation and supports an AI auditor in assessing
if the system complies with conformity requirements.
A standardized transparency taxonomy of AI systems helps people with different backgrounds to better
understand each other by using the same terminology. This in turn supports an improved understanding of AI
systems, and provides a foundation for developing interoperable and coherent transparency related
standards.
This document is structured as follows:
— 5— Clause 5 provides an overview of this document and describes the concept of transparency of AI
systems;
— 6— Clause 6 discusses how transparency needs can vary depending on the AI system context and on the
stakeholders involved;
— 7— Clause 7 discusses transparency items that describe the context of the AI system;
— 8— Clause 8 pertains to describing transparency disclosures at the AI system level;
— 9— Clause 9 focuses on documenting the internal functioning of the system;
— 10— Clause 10 offers guidance on the documentation of datasets as stand-alone items.
AI systems often affect society and the environment (see 7Clause 7).). However, it is also true that society and
the environment can affect the performance of an AI system. This can include various aspects, such as:
— — environmental conditions that affect the functioning and longevity of an AI system;
— — introduction or reinforcement of unwanted bias;
— — organizational practices that can cause poor outcomes;
© ISO/IEC 20242025 – All rights reserved
vi
ISO/IEC DISFDIS 12792:20242025(en)
— — effects such as concept drift (concept drift occurs when there is a change in the functional relationship
between the model’s input and output) and data drift (data drift i
...
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