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  Steering open-source AI to accelerate the sustainable development goals [Comment]

Chen, M., Wu, K., Pradhan, P., Allen, C., Nativi, S., Hubacek, K., Voinov, A., Creutzig, F., Filatova, T., Boers, N., Meadows, M., Ma, P., Biermann, F., Schellnhuber, H. J., Ludden, J., Paradiso, M., Batty, M., Guo, H., Cao, M., Hou, P., Lü, G. (2026): Steering open-source AI to accelerate the sustainable development goals [Comment]. - Nature Communications, 17, 4959.
https://doi.org/10.1038/s41467-026-73866-8

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Chen_2026_s41467-026-73866-8.pdf (Publisher version), 634KB
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Chen_2026_s41467-026-73866-8.pdf
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 Creators:
Chen, Min1, Author
Wu, Kai1, Author
Pradhan, Prajal2, Author                 
Allen, Cameron1, Author
Nativi, Stefano1, Author
Hubacek, Klaus1, Author
Voinov, Alexey1, Author
Creutzig, Felix2, Author                 
Filatova, Tatiana1, Author
Boers, Niklas2, Author                 
Meadows, Michael1, Author
Ma, Peilong1, Author
Biermann, Frank1, Author
Schellnhuber, Hans Joachim1, Author
Ludden, John1, Author
Paradiso, Maria1, Author
Batty, Michael1, Author
Guo, Huadong1, Author
Cao, Min1, Author
Hou, Peng1, Author
Lü, Guonian1, Author more..
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: While the artificial intelligence (AI) revolution is advancing rapidly, the open-source paradigm offers key pathways and potential risks for accelerating progress towards the Sustainable Development Goals and beyond. This comment introduces four governance actions that consider how sustainability, evaluation, safety, and cooperation can be integrated into the transformation of open-source AI, thereby reducing uncertainties and challenges posed by open-source AI for sustainable global prosperity.

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Language(s): eng - English
 Dates: 2026-06-112026-06-11
 Publication Status: Finally published
 Pages: 5
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41467-026-73866-8
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
PIKDOMAIN: RD2 - Climate Resilience
Organisational keyword: RD2 - Climate Resilience
PIKDOMAIN: RD5 - Climate Economics and Policy - MCC Berlin
Organisational keyword: RD5 - Climate Economics and Policy - MCC Berlin
Working Group: Artificial Intelligence
Model / method: Machine Learning
OATYPE: Gold Open Access
 Degree: -

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Title: Nature Communications
Source Genre: Journal, SCI, Scopus, oa
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Pages: - Volume / Issue: 17 Sequence Number: 4959 Start / End Page: - Identifier: Publisher: Nature
CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals354