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Using generative AI to increase sceptics’ engagement with climate science

Nature Climate Change (2025)Cite this article

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Abstract

Climate scepticism remains an important barrier to public engagement with accurate climate information, because sceptics often actively avoid information that contains climate science facts. There still lacks a scalable, repeatable intervention to boost sceptics’ engagement with climate information. Here we show that generative artificial intelligence can enhance engagement with climate science among sceptical audiences by subtly modifying headlines to reduce anticipated disagreement, regret and negative emotions, without compromising factual integrity. Headlines of climate science articles modified by an open-source large language model led to more bookmarks and more upvotes, and these effects were strongest among the most sceptical participants. Participants who engaged with climate science as a result of this intervention showed a shift in beliefs towards alignment with the scientific consensus. These results show that generative artificial intelligence can alter the information diet sceptics consume and holds promise for advancing public understanding of science when responsibly deployed by well-intentioned actors.

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Fig. 1: Experimental methods.
Fig. 2: Main results on the engagement of sceptics with climate news.
Fig. 3: Participants’ shift towards alignment with the scientific consensus at the end of the study for three beliefs.

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Data availability

The data are available via GitHub at https://github.com/bencebago/climate_headlines_personalization/tree/main/data ref. 77.

Code availability

The code for the analysis and all materials is available via GitHub at https://github.com/bencebago/climate_headlines_personalization/tree/main/analysis.

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Acknowledgements

J.F.B. acknowledges support from grant nos. ANR-23-IACL-0002, ANR-17-EURE-0010 and ANR-22-CE26-0014-01 and the research foundation TSE-Partnership. We gratefully acknowledge the help of Iyad Rahwan at the Center of Humans and Machines, Max Planck Institute for Human Development, for obtaining funding for data collection.

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Authors and Affiliations

  1. Department of Social Psychology, Tilburg University, Tilburg, the Netherlands

    Bence Bago

  2. Institut de Recherche en Informatique de Toulouse, Université de Toulouse, Toulouse, France

    Philippe Muller

  3. Toulouse School of Economics, CNRS, Université Toulouse Capitole, Toulouse, France

    Jean-François Bonnefon

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  1. Bence Bago
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  2. Philippe Muller
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  3. Jean-François Bonnefon
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Contributions

The study was conceptualized by B.B., J.F.B. and P.M., who also developed the methodology and conducted the investigation together. B.B. was responsible for curating the data, conducting the formal analysis and developing the experimental software. J.F.B. secured the funding for this research and created the visualizations. The original draft of the manuscript was written by B.B. and J.F.B., while all three authors participated in reviewing and editing the final manuscript.

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Correspondence to Bence Bago.

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Nature Climate Change thanks Carmen Atkins, Mike Schäfer and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Figs. 1 and 2, Tables 1–59, analyses and materials.

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Bago, B., Muller, P. & Bonnefon, JF. Using generative AI to increase sceptics’ engagement with climate science. Nat. Clim. Chang. (2025). https://doi.org/10.1038/s41558-025-02424-9

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