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Prioritize environmental sustainability in use of AI and data science methods

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Artificial Intelligence (AI) and data science will play a crucial role in improving environmental sustainability, but the energy requirements of these methods will have an increasingly negative effect on the environment without sustainable design and use.

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Fig. 1: Recognizing the environmental impact of computational environmental science research.

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Acknowledgements

The workshop that generated the ideas for this comment was supported by the Alan Turing Institute. C.J. was supported by the Software Sustainability Institute grant EP/S021779/1. C.J. and D.T. were supported by the NERC Digital Solutions Programme. L.L. was supported by core funding from the British Heart Foundation (RG/18/13/33946); the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014; NIHR203312); the Cambridge British Heart Foundation Centre of Research Excellence (RE/18/1/34212); and the BHF Chair Award (CH/12/2/29428). E.L. was funded by a UKRI Future Leaders Fellowship (MR/T019832/1). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

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Authors and Affiliations

  1. School of Engineering, University of Manchester, Manchester, UK

    Caroline Jay

  2. Software Sustainability Institute, Edinburgh, UK

    Caroline Jay, Robert Haines & Loïc Lannelongue

  3. Alan Turing Institute, London, UK

    Caroline Jay, Gavin Shaddick, Emily Lines, Scott Hosking & David Topping

  4. Centre for Environmental Policy, Imperial College London, London, UK

    Yurong Yu

  5. School of Natural Sciences, University of Manchester, Manchester, UK

    Ian Crawford & David Topping

  6. Research IT, University of Manchester, Manchester, UK

    Scott Archer-Nicholls, Ann Gledson & Robert Haines

  7. School of Engineering, University of Newcastle, Newcastle, UK

    Philip James

  8. School of Engineering, Physical and Mathematical Sciences, Royal Holloway University of London, London, UK

    Gavin Shaddick

  9. Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

    Loïc Lannelongue

  10. British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

    Loïc Lannelongue

  11. Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK

    Loïc Lannelongue

  12. Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK

    Loïc Lannelongue

  13. Department of Geography, University of Cambridge, Cambridge, UK

    Emily Lines

  14. British Antarctic Survey, Cambridge, UK

    Scott Hosking

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  1. Caroline Jay
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  2. Yurong Yu
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  3. Ian Crawford
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  4. Scott Archer-Nicholls
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  6. Ann Gledson
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  7. Gavin Shaddick
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  8. Robert Haines
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  9. Loïc Lannelongue
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  10. Emily Lines
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  11. Scott Hosking
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  12. David Topping
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Corresponding author

Correspondence to Caroline Jay.

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The authors declare no competing interests.

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Jay, C., Yu, Y., Crawford, I. et al. Prioritize environmental sustainability in use of AI and data science methods. Nat. Geosci. 17, 106–108 (2024). https://doi.org/10.1038/s41561-023-01369-y

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