AI ethics: a framework for measuring embodied carbon in AI systems
File(s)
Published version
Author(s)
Mulligan, Catherine
Elaluf-Calderwood, Silvia
Type
Journal Article
Abstract
This paper outlines the ethical implications of AI from a climate perspective. So far, much of the discussion around AI ethics have focused on bias, unexplainable outcomes, privacy and other social impacts of such systems. The role and contribution of AI towards climate change and the ethical implications of its contribution to an unjust distribution of impact on the planet, humans and flora and fauna have not yet been covered in detail within the technical community. Within this paper, we aim to raise some of the issues of AI associated with climate justice and we propose a framework that will allow the AI and ICT industries to measure their true impact on the planet, propose an organisational structure to take this work forward and propose future research areas for this important topic.
Date Issued
2022-08
Date Acceptance
2021-06-08
Citation
AI and Ethics, 2022, 2 (3), pp.363-375
ISSN
2730-5961
Publisher
Springer
Start Page
363
End Page
375
Journal / Book Title
AI and Ethics
Volume
2
Issue
3
Copyright Statement
© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
http://dx.doi.org/10.1007/s43681-021-00071-2
Publication Status
Published
Date Publish Online
2021-06-21