Unraveling the Hidden Environmental Impacts of AI Solutions for Environment Life Cycle Assessment of AI Solutions

Anne-Laure Ligozat, Julien Lefevre, Aurélie Bugeau and Jacques Combaz
Additional contact information
Anne-Laure Ligozat: Université Paris-Saclay, CNRS, ENSIIE, Laboratoire Interdisciplinaire des Sciences du Numérique, 91400 Orsay, France
Julien Lefevre: Aix Marseille Univ., CNRS, INT, Inst Neurosci Timone, 13005 Marseille, France
Aurélie Bugeau: Univ. Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR5800, 33400 Talence, France
Jacques Combaz: Univ. Grenoble Alpes, CNRS, Grenoble INP, VERIMAG, 38000 Grenoble, France

Sustainability, 2022, vol. 14, issue 9, 1-14

Abstract: In the past ten years, artificial intelligence has encountered such dramatic progress that it is now seen as a tool of choice to solve environmental issues and, in the first place, greenhouse gas emissions (GHG). At the same time, the deep learning community began to realize that training models with more and more parameters require a lot of energy and, as a consequence, GHG emissions. To our knowledge, questioning the complete net environmental impacts of AI solutions for the environment (AI for Green) and not only GHG, has never been addressed directly. In this article, we propose to study the possible negative impacts of AI for Green. First, we review the different types of AI impacts; then, we present the different methodologies used to assess those impacts and show how to apply life cycle assessment to AI services. Finally, we discuss how to assess the environmental usefulness of a general AI service and point out the limitations of existing work in AI for Green.

Keywords: artificial intelligence; sustainability; carbon footprint; LCA (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/9/5172/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/9/5172/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:9:p:5172-:d:801671

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().