FprCEN/CLC/TR 18145

SLOVENSKI STANDARD
01-december-2024
Okoljsko trajnostna umetna inteligenca
Environmentally sustainable Artificial Intelligence
Informationstechnik - Künstliche Intelligenz - Grüne und nachhaltige KI
Ta slovenski standard je istoveten z: FprCEN/CLC/TR 18145
ICS:
13.020.20 Okoljska ekonomija. Environmental economics.
Trajnostnost Sustainability
35.020 Informacijska tehnika in Information technology (IT) in
tehnologija na splošno general
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

TECHNICAL REPORT FINAL DRAFT
RAPPORT TECHNIQUE
TECHNISCHER REPORT
October 2024
ICS
English version
Environmentally sustainable Artificial Intelligence
Informationstechnik ¿ Künstliche Intelligenz ¿ Grüne
und nachhaltige KI
This draft Technical Report is submitted to CEN members for Vote. It has been drawn up by the Technical Committee
CEN/CLC/JTC 21.
CEN and CENELEC members are the national standards bodies and national electrotechnical committees of Austria, Belgium,
Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy,
Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Republic of North Macedonia, Romania, Serbia,
Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and United Kingdom.

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 supporting documentation.

Warning : This document is not a Technical Report. It is distributed for review and comments. It is subject to change without
notice and shall not be referred to as a Technical Report.

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© 2024 CEN/CENELEC All rights of exploitation in any form and by any means
Ref. No. FprCEN/CLC/TR 18145:2024 E
reserved worldwide for CEN national Members and for
CENELEC Members.
FprCEN/CLC TR 18145:2024(E)
Contents Page
European foreword . 3
1 Scope . 4
2 Normative references . 4
3 Terms, definitions and abbreviated terms . 5
3.1 Terms and definitions . 5
3.1.1 Terms related to Artificial intelligence and Machine Learning . 5
3.1.2 Terms related to environmental sustainability . 6
3.2 Abbreviated terms . 6
4 Environmental impacts . 7
4.1 General. 7
4.2 A definition of the issue . 7
4.3 European energy infrastructure . 8
5 Energy resources and AI . 10
5.1 General. 10
5.2 Energy consumption by AI . 10
5.3 AI energy efficiency methods . 12
5.3.1 Software solutions . 12
5.3.2 Hardware solutions . 14
5.3.3 Location solutions . 15
6 Non-energy resources and AI . 15
6.1 General. 15
6.2 AI Water use and pollution . 15
6.3 Resources for hardware . 16
6.4 Land use and soil pollution . 16
6.5 Guidance on mitigation solutions . 16
6.5.1 Creating awareness . 16
6.5.2 Considering the complete lifecycle . 17
6.5.3 Circular economy . 17
6.6 Policymaking for mitigation of AI environmental impact . 17
7 Environmental benefits of using AI . 18
7.1 General. 18
7.2 Use cases of energy savings . 18
7.2.1 General. 18
7.2.2 Optimizing the use of natural resources . 18
7.2.3 Helping to manage climate change . 18
7.2.4 AI and sustainable networks in ICT . 19
7.3 Use cases that save other resources . 19
8 Quantification of AI environmental sustainability . 19
8.1 General. 19
8.2 AI carbon footprint estimation . 21
8.3 Comparative measures of efficiency . 24
Bibliography . 26
FprCEN/CLC TR 18145:2024 (E)
European foreword
This document (FprCEN/CLC/TR 18145:2024) has been prepared by Technical Committee
CEN/CLC/JTC 21 “Artificial Intelligence”, the secretariat of which is held by DS.
This document is currently submitted to the Vote on TR.
FprCEN/CLC TR 18145:2024(E)
1 Scope
This document provides a description of the main environmental sustainability issues that organisations
or individuals that are developing and/or using Artificial Intelligence (AI) consider, in particular, in the
context of the European energy systems and resources.
It is important to have a focus where AI helps in optimization and virtual deployment of engineering
solutions [1], especially in Europe with limited natural resources. This document reviews the European
AI landscape, with a context of environmental sustainability. This is addressed with a focus on European-
specific aspects of AI demands for resources, as well as its potential to contribute to environmental
sustainability in Europe [2]. The document creates an inventory of impacts and techniques to support
environmentally sustainable use of AI, and an equitable access to computation resources.
Suggested improvements in AI resource management are focused on:
• reduction of the operational AI energy consumption (see section 5)
• reduction of other AI resource consumption (water, etc.) (see section 6)
The document also considers the potential benefits of using AI from a sustainability perspective. Methods
of measuring the environmental sustainability impacts of AI are also quantified.
This document is intended to help with the development of new standards and complement existing
European standards and standardization deliverables that define resource measurement for the use of
AI. It describes best practices and indicates which techniques and management processes for
improvement of AI resource performance and environmental viability. The document is expected to
contribute to voluntary corporate social responsibility (CSR) in Europe, and increase sustainability
awareness for individuals when designing, developing, and using AI. The aim is to create a focus on the
responsible use of AI that prioritizes ethical considerations, human values, and an understanding of the
social implications of AI design and use.
The document is aligned with equivalent activities in ISO/IEC/JTC 1/SC42/WG4, TR 20226 “Green and
Sustainable AI”, but takes into account specific aspects of the European energy system that are not
applicable elsewhere. In particular, sustainable energy supply provided via the European interconnectors
will be taken into account when assessing AI carbon footprint. Additionally AI solutions for the
optimization of energy use will be reviewed and quantified to balance the energy use of AI applications
and services which make extensive use of energy. This report also identifies and addresses the United
Nations Sustainable Development Goals [3, 4]. Additionally, this document aligns with ISO/IEC DIS 21031
Information Technology – Software Carbon Intensity (SCI) [5], ISO/DIS 59004 Circular Economy –
Terminology, Principles and Guidance for Implementation, and the Greenhouse Gas Protocol (GHG),
Product Life Cycle Accounting and Reporting Standard [6].
The upcoming EU AI Act in its current draft encourages voluntary assessment of companies for
environmental sustainability.
2 Normative references
There are no normative references in this document.
FprCEN/CLC TR 18145:2024 (E)
3 Terms, definitions and abbreviated terms
For the purposes of this document, the following terms and definitions apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https://www.iso.org/obp/
— IEC Electropedia: available at https://www.electropedia.org/
3.1 Terms and definitions
3.1.1 Terms related to Artificial intelligence and Machine Learning
3.1.1.1
artificial intelligence
AI
research and development of mechanisms and applications of AI systems
Note 1 to entry: Research and development can take place across a number of fields such as computer science, data
science, humanities, mathematics and natural sciences.
[SOURCE: ISO/IEC 22989:2022]
3.1.1.2
artificial intelligence system
AI system
engineered system that generates outputs such as content, forecasts, recommendations or decisions for
a given set of human-defined objectives
Note 1 to entry: The engineered system can use various techniques and approaches related artificial intelligence to
develop a model to represent data, knowledge, process, etc which can be used to conduct tasks.
Note 2 to entry: AI systems are designed to operate with varying levels of automation.
[SOURCE: ISO/IEC 22989:2022]
3.1.1.3
dark data
information assets that organizations collect, process and store during regular business activities, but fail
to use for purposes beyond those associated with the initial collection
3.1.1.4
internet of things
IoT
infrastructure of interconnected entities, people, systems, and information resources together with
services which processes and reacts to information from the physical world and virtual world
[SOURCE: ISO/IEC 20924:2021]
FprCEN/CLC TR 18145:2024(E)
3.1.1.5
machine learning
ML
process of optimizing model parameters through computational techniques, such that the model's
behaviour reflects the data or experience
[SOURCE: ISO/IEC 22989:2022]
3.1.2 Terms related to environmental sustainability
3.1.2.1
environmental sustainability
state in which the ecosystem and its functions are maintained for the present and future generation
[SOURCE: ISO 17889-1:2021]
3.1.2.2
life cycle
evolution of a system, product, service, project or other human-made entity from conception through
retirement
[SOURCE: ISO/IEC/IEEE 15288:2015: Systems and software engineering — Software life cycle proce
...