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  Artificial intelligence in sustainable development research

Gohr, C., Rodríguez, G., Belomestnykh, S., Berg-Moelleken, D., Chauhan, N., Engler, J.-O., Heydebreck, L. V., Hintz, M. J., Kretschmer, M., Krügermeier, C., Meinberg, J., Rau, A.-L., Schwenck, C., Aoulkadi, I., Poll, S., Frank, E., Creutzig, F., Lemke, O., Maushart, M., Pfendtner-Heise, J., Rathgens, J., von Wehrden, H. (2025): Artificial intelligence in sustainable development research. - Nature Sustainability, 8, 970-978.
https://doi.org/10.1038/s41893-025-01598-6

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Gohr, C.1, Autor
Rodríguez, G.1, Autor
Belomestnykh, S.1, Autor
Berg-Moelleken, D.1, Autor
Chauhan, N.1, Autor
Engler, J.-O.1, Autor
Heydebreck, L. V.1, Autor
Hintz, Marie Josefine2, Autor           
Kretschmer, M.1, Autor
Krügermeier, C.1, Autor
Meinberg, J.1, Autor
Rau, A.-L.1, Autor
Schwenck, C.1, Autor
Aoulkadi, I.1, Autor
Poll, S.1, Autor
Frank, E.1, Autor
Creutzig, Felix2, Autor                 
Lemke, O.1, Autor
Maushart, M.1, Autor
Pfendtner-Heise, J.1, Autor
Rathgens, J.1, Autorvon Wehrden, H.1, Autor mehr..
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, Potsdam, ou_persistent13              

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 Zusammenfassung: Artificial intelligence (AI) holds significant potential to advance Sustainable Development Goals by enabling data-driven insights and optimizations. In this analysis, we review 792 articles that explore AI applications in Sustainable Development Goal-related research. The literature is organized along two dimensions: (1) the disciplinary spectrum, from natural sciences to the humanities, and (2) the focus, distinguishing economic from socioecological content. Deep learning and supervised machine learning were the most prominently applied algorithms for forecasting and system optimization. However, we identify a critical gap: only a few studies combine advanced AI applications with deep sustainability expertise. Sustainability needs to strike a balance between contextualization and generalizability to provide tangible knowledge that will lead to responsible change. AI must play a central role in this process. While expectations for AI’s transformative role in sustainable development are high, its full potential remains to be realized.

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Sprache(n): eng - English
 Datum: 2025-01-062025-06-112025-07-212025-08-01
 Publikationsstatus: Final veröffentlicht
 Seiten: 12
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1038/s41893-025-01598-6
PIKDOMAIN: RD5 - Climate Economics and Policy - MCC Berlin
Organisational keyword: RD5 - Climate Economics and Policy - MCC Berlin
Working Group: Cities: Data Science and Sustainable Planning
Research topic keyword: Sustainable Development
Model / method: Machine Learning
MDB-ID: No MDB - stored outside PIK (see locators/paper)
OATYPE: Hybrid Open Access
 Art des Abschluß: -

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Quelle 1

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Titel: Nature Sustainability
Genre der Quelle: Zeitschrift, SCI, Scopus
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 8 Artikelnummer: - Start- / Endseite: 970 - 978 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/nature-sustainability
Publisher: Nature