Towards the Sustainability of AI; Multi-Disciplinary Approaches to Investigate the Hidden Costs of AI

Our era is characterized by two major phenomena. On the one hand, we are confronted by climate and environmental crises constituted by, among others, changing weather patterns, loss of biodiversity and natural wildlife, and ecosystem degradation. On the other hand, we are experiencing an ongoing tec...

Disgrifiad llawn

Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Fformat: Online
Iaith:Saesneg
Cyhoeddwyd: MDPI - Multidisciplinary Digital Publishing Institute 2023
Pynciau:
Mynediad Ar-lein:ONIX_20230405_9783036566009_245
Tagiau: Ychwanegu Tag
Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!
_version_ 1869521502603313152
collection Directory of Open Access Books
description Our era is characterized by two major phenomena. On the one hand, we are confronted by climate and environmental crises constituted by, among others, changing weather patterns, loss of biodiversity and natural wildlife, and ecosystem degradation. On the other hand, we are experiencing an ongoing technological evolution culminating in the rise of artificial intelligence (AI). The popular notion of “AI for Sustainability” constitutes an attempt to connect these two phenomena in a beneficial way by using AI to alleviate climate and environmental worries. AI is increasingly being used in the analysis, mitigation, and prevention of the climate and environmental crises and their effects. Much less attention has been paid to the idea of the “Sustainability of AI”, which focusses on the materiality of AI technologies themselves. Indeed, what are the hidden costs of AI? Although we use AI in combatting the climate and environmental crises, does it not have its own contributions to these crises? And, if so, how do we account for these contributions? The Special Issue is the first attempt to address the topic of “Sustainable AI” from a multi-disciplinary perspective. The authors that contributed to this issue come from diverse fields such as philosophy, ethics, sociology, law, and engineering. The included papers represent the first steps in understanding what it means to tackle the climate and environmental crises with AI while refraining from aggravating these crises.
format Online
id doab-20.500.12854ir-98966
institution Directory of Open Access Books
language eng
publishDate 2023
publishDateRange 2023
publishDateSort 2023
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
record_format ojs
spelling doab-20.500.12854ir-989662024-04-09T23:16:07Z Towards the Sustainability of AI; Multi-Disciplinary Approaches to Investigate the Hidden Costs of AI van Wynsberghe, Aimee Vandemeulebroucke, Tijs Bolte, Larissa Nachid, Jamila artificial intelligence Sustainable Development Goals ESG CSR reporting disclosure sustainability sustainable AI greenwashing unfair commercial practices AI Act digitalization sustainable digitalization sustainable development SDGs Assessment Framework mindful digital age digitainability digital technologies qualitative research environmental impact carboncentric technocentric surrogate-based optimisation surrogate model sequential model-based optimisation Bayesian optimisation Green AI machine learning intergenerational justice future generations policy-making explainability transparency AI AI governance ethics ethical AI differential privacy AI certification ethics of AI AI ethics checklist ethics ethics of carefulness ethics of desirability climate justice infrastructure climate change nudging digital nudging libertarian paternalism autonomy carbon footprint LCA n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Our era is characterized by two major phenomena. On the one hand, we are confronted by climate and environmental crises constituted by, among others, changing weather patterns, loss of biodiversity and natural wildlife, and ecosystem degradation. On the other hand, we are experiencing an ongoing technological evolution culminating in the rise of artificial intelligence (AI). The popular notion of “AI for Sustainability” constitutes an attempt to connect these two phenomena in a beneficial way by using AI to alleviate climate and environmental worries. AI is increasingly being used in the analysis, mitigation, and prevention of the climate and environmental crises and their effects. Much less attention has been paid to the idea of the “Sustainability of AI”, which focusses on the materiality of AI technologies themselves. Indeed, what are the hidden costs of AI? Although we use AI in combatting the climate and environmental crises, does it not have its own contributions to these crises? And, if so, how do we account for these contributions? The Special Issue is the first attempt to address the topic of “Sustainable AI” from a multi-disciplinary perspective. The authors that contributed to this issue come from diverse fields such as philosophy, ethics, sociology, law, and engineering. The included papers represent the first steps in understanding what it means to tackle the climate and environmental crises with AI while refraining from aggravating these crises. 2023-04-05T13:01:23Z 2023-04-05T13:01:23Z 2023 book ONIX_20230405_9783036566009_245 9783036566009 9783036566016 https://directory.doabooks.org/handle/20.500.12854/98966 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/7019 https://mdpi.com/books/pdfview/book/7019 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-6601-6 10.3390/books978-3-0365-6601-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036566009 9783036566016 190 Basel open access
spellingShingle artificial intelligence
Sustainable Development Goals
ESG
CSR
reporting
disclosure
sustainability
sustainable AI
greenwashing
unfair commercial practices
AI Act
digitalization
sustainable digitalization
sustainable development
SDGs
Assessment Framework
mindful
digital age
digitainability
digital technologies
qualitative research
environmental impact
carboncentric
technocentric
surrogate-based optimisation
surrogate model
sequential model-based optimisation
Bayesian optimisation
Green AI
machine learning
intergenerational justice
future generations
policy-making
explainability
transparency
AI
AI governance
ethics
ethical AI
differential privacy
AI certification
ethics of AI
AI ethics
checklist ethics
ethics of carefulness
ethics of desirability
climate justice
infrastructure
climate change
nudging
digital nudging
libertarian paternalism
autonomy
carbon footprint
LCA
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Towards the Sustainability of AI; Multi-Disciplinary Approaches to Investigate the Hidden Costs of AI
title Towards the Sustainability of AI; Multi-Disciplinary Approaches to Investigate the Hidden Costs of AI
title_full Towards the Sustainability of AI; Multi-Disciplinary Approaches to Investigate the Hidden Costs of AI
title_fullStr Towards the Sustainability of AI; Multi-Disciplinary Approaches to Investigate the Hidden Costs of AI
title_full_unstemmed Towards the Sustainability of AI; Multi-Disciplinary Approaches to Investigate the Hidden Costs of AI
title_short Towards the Sustainability of AI; Multi-Disciplinary Approaches to Investigate the Hidden Costs of AI
title_sort towards the sustainability of ai multi disciplinary approaches to investigate the hidden costs of ai
topic artificial intelligence
Sustainable Development Goals
ESG
CSR
reporting
disclosure
sustainability
sustainable AI
greenwashing
unfair commercial practices
AI Act
digitalization
sustainable digitalization
sustainable development
SDGs
Assessment Framework
mindful
digital age
digitainability
digital technologies
qualitative research
environmental impact
carboncentric
technocentric
surrogate-based optimisation
surrogate model
sequential model-based optimisation
Bayesian optimisation
Green AI
machine learning
intergenerational justice
future generations
policy-making
explainability
transparency
AI
AI governance
ethics
ethical AI
differential privacy
AI certification
ethics of AI
AI ethics
checklist ethics
ethics of carefulness
ethics of desirability
climate justice
infrastructure
climate change
nudging
digital nudging
libertarian paternalism
autonomy
carbon footprint
LCA
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
topic_facet artificial intelligence
Sustainable Development Goals
ESG
CSR
reporting
disclosure
sustainability
sustainable AI
greenwashing
unfair commercial practices
AI Act
digitalization
sustainable digitalization
sustainable development
SDGs
Assessment Framework
mindful
digital age
digitainability
digital technologies
qualitative research
environmental impact
carboncentric
technocentric
surrogate-based optimisation
surrogate model
sequential model-based optimisation
Bayesian optimisation
Green AI
machine learning
intergenerational justice
future generations
policy-making
explainability
transparency
AI
AI governance
ethics
ethical AI
differential privacy
AI certification
ethics of AI
AI ethics
checklist ethics
ethics of carefulness
ethics of desirability
climate justice
infrastructure
climate change
nudging
digital nudging
libertarian paternalism
autonomy
carbon footprint
LCA
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
url ONIX_20230405_9783036566009_245