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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/islightboxThumbnailVersionOf https://pure.iiasa.ac.at/id/document/111770 111777 2 337798 document 111777 preview.jpg image/png 5cea5b6b0105e2470aba49f94eb26922 MD5 20813 2025-11-19 10:21:51 https://pure.iiasa.ac.at/id/eprint/21000/3/preview.jpg 21000 3 3 image/png other Thumbnails conversion from text to thumbnail_preview en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/ispreviewThumbnailVersionOf https://pure.iiasa.ac.at/id/document/111770 111778 2 337799 document 111778 medium.jpg image/png cb4ba775c724f2eef6f49176eaea3489 MD5 9594 2025-11-19 10:21:52 https://pure.iiasa.ac.at/id/eprint/21000/4/medium.jpg 21000 4 4 image/png other Thumbnails conversion from text to thumbnail_medium en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/ismediumThumbnailVersionOf https://pure.iiasa.ac.at/id/document/111770 111779 2 337800 document 111779 small.jpg image/png 8429cbcc62ab35fb168f112845b62503 MD5 2668 2025-11-19 10:21:52 https://pure.iiasa.ac.at/id/eprint/21000/5/small.jpg 21000 5 5 image/png other Thumbnails conversion from text to thumbnail_small en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/111770 111780 1 337801 document 111780 indexcodes.txt text/x-c b7734f4b8c1081a8981cbcbd09ce1072 MD5 27465 2025-11-19 10:21:59 https://pure.iiasa.ac.at/id/eprint/21000/6/indexcodes.txt 21000 6 6 text/x-c other Generate index codes conversion from text to indexcodes en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/111770 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/111770 archive 353 disk0/00/02/10/00 2025-11-19 10:13:33 2025-11-19 10:13:33 2025-11-19 10:13:33 article show Tiggeloven T. Pfeiffer S. Matanó A. van den Homberg M. Thalheimer L. 9331 0000-0002-3737-3586 Reichstein M. Torresan S. pub POPJUS MIG Artificial intelligence (AI) is gaining momentum in earth sciences as a tool to analyze complex natural hazards and their impacts. Such analyses are critical for effective Early Warning Systems (EWSs), which is aiming to generate timely and actionable risk information to protect sectors, systems, and people. Despite advancements in AI, its role in EWS remains underexplored across the four pillars of the Early Warning for All (EW4All) framework; risk knowledge, forecasting, warning dissemination and communication and response preparedness. This study draws on a systematic literature review to assess AI methods utilized in the context of EWS, examines their challenges and opportunities and discusses guiding questions for responsible use. Our study highlights key gaps across knowledge, application and policy. Moreover, we call for coordinated efforts to develop responsible AI frameworks that enhance EWS while ensuring they remain inclusive, accessible, and people-centred that ultimately supports the goal of EW4All by 2027. 2025-11 published doi:10.1016/j.isci.2025.113689 3268 public iScience 28 11 e113689 1 TRUE 2589-0042 info:eu-repo/semantics/article