kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
The Potential of Artificial Intelligence for Achieving Healthy and Sustainable Societies
Smart Cities, School of Creative Technologies, Saxion University of Applied Sciences, Enschede, The Netherlands.
Bonn Alliance for Sustainability Research, University of Bonn, Bonn, Germany.
KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW. KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Fluid Mechanics and Engineering Acoustics.ORCID iD: 0000-0003-4109-0009
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0001-5211-6388
Show others and affiliations
Number of Authors: 132023 (English)In: The Ethics of Artificial Intelligence for the Sustainable Development Goals / [ed] Francesca Mazzi, Luciano Floridi, Springer Nature , 2023, Vol. 152, p. 65-96Chapter in book (Other academic)
Abstract [en]

In this chapter we extend earlier work (Vinuesa et al., Nat Commun 11, 2020) on the potential of artificial intelligence (AI) to achieve the 17 Sustainable Development Goals (SDGs) proposed by the United Nations (UN) for the 2030 Agenda. The present contribution focuses on three SDGs related to healthy and sustainable societies, i.e., SDG 3 (on good health), SDG 11 (on sustainable cities), and SDG 13 (on climate action). This chapter extends the previous study within those three goals and goes beyond the 2030 targets. These SDGs are selected because they are closely related to the coronavirus disease 19 (COVID-19) pandemic and also to crises like climate change, which constitute important challenges to our society.

Place, publisher, year, edition, pages
Springer Nature , 2023. Vol. 152, p. 65-96
Series
Philosophical Studies Series, ISSN 0921-8599, E-ISSN 2542-8349
Keywords [en]
AI, SDGs
National Category
Economics Other Social Sciences not elsewhere specified
Identifiers
URN: urn:nbn:se:kth:diva-333065DOI: 10.1007/978-3-031-21147-8_5Scopus ID: 2-s2.0-85158127117OAI: oai:DiVA.org:kth-333065DiVA, id: diva2:1784025
Note

Part of book ISBN 978-3-031-21147-8

QC 20230725

Available from: 2023-07-25 Created: 2023-07-25 Last updated: 2025-05-05Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopusarXiv

Authority records

Mallor, FerminAzizpour, HosseinBan, YifangEivazi, HamidrezaFang, HengGolzar, FarzinLeite, IolandaMelsión, Gaspar IsaacSmith, KevinNerini, Francesco FusoVinuesa, Ricardo

Search in DiVA

By author/editor
Mallor, FerminAzizpour, HosseinBan, YifangEivazi, HamidrezaFang, HengGolzar, FarzinLeite, IolandaMelsión, Gaspar IsaacSmith, KevinNerini, Francesco FusoVinuesa, Ricardo
By organisation
Linné Flow Center, FLOWFluid Mechanics and Engineering AcousticsRobotics, Perception and Learning, RPLGeoinformaticsEngineering MechanicsEnergy SystemsKTH Climate Action Centre, CAC
EconomicsOther Social Sciences not elsewhere specified

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 183 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf