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Data Science and AI for Sustainable Futures: Opportunities and Challenges

Author

Listed:
  • Gavin Shaddick

    (College of Physical Sciences and Engineering, Cardiff University, Cardiff CF10 3AT, UK)

  • David Topping

    (School of Earth and Environmental Science, University of Manchester, Manchester M13 9PL, UK)

  • Tristram C. Hales

    (School of Earth and Environmental Sciences, Cardiff University, Cardiff CF10 3AT, UK)

  • Usama Kadri

    (School of Mathematics, Cardiff University, Cardiff CF24 4AG, UK)

  • Joanne Patterson

    (Welsh School of Architecture, Cardiff University, Cardiff CF10 3BN, UK)

  • John Pickett

    (School of Chemistry, Cardiff University, Cardiff CF10 3AT, UK)

  • Ioan Petri

    (School of Engineering, Cardiff University, Cardiff CF24 3AA, UK)

  • Stuart Taylor

    (School of Chemistry, Cardiff University, Cardiff CF10 3AT, UK)

  • Peiyuan Li

    (Discovery Partners Institute, University of Illinois System, Chicago, IL 60606, USA)

  • Ashish Sharma

    (Discovery Partners Institute, University of Illinois System, Chicago, IL 60606, USA)

  • Venkat Venkatkrishnan

    (Discovery Partners Institute, University of Illinois System, Chicago, IL 60606, USA)

  • Abhinav Wadhwa

    (Discovery Partners Institute, University of Illinois System, Chicago, IL 60606, USA)

  • Jennifer Ding

    (The Alan Turing Institute, London NW1 2DB, UK)

  • Ruth Bowyer

    (Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK)

  • Omer Rana

    (School of Computer Science and Informatics, Cardiff University, Cardiff CF24 4AG, UK)

Abstract

Advances in data science and artificial intelligence (AI) offer unprecedented opportunities to provide actionable insights, drive innovative solutions, and create long-term strategies for sustainable development in response to the triple existential crises facing humanity: climate change, pollution, and biodiversity loss. The rapid development of AI models has been the subject of extensive debate and is high on the political agenda, but at present the vast potential for AI to contribute positively to informed decision making, improved environmental risk management, and the development of technological solutions to sustainability challenges remains underdeveloped. In this paper, we consider four inter-dependent areas in which data science and AI can make a substantial contribution to developing sustainable future interactions with the environment: (i) quantification and tracking progress towards the United Nations Sustainable Development Goals; (ii) embedding AI technologies to reduce emissions at source; (iii) developing systems to increase our resilience to natural hazards; (iv) Net Zero and the built environment. We also consider the wider challenges associated with the widespread use of AI, including data access and discoverability, trust and regulation, inference and decision making, and the sustainable use of AI.

Suggested Citation

  • Gavin Shaddick & David Topping & Tristram C. Hales & Usama Kadri & Joanne Patterson & John Pickett & Ioan Petri & Stuart Taylor & Peiyuan Li & Ashish Sharma & Venkat Venkatkrishnan & Abhinav Wadhwa & , 2025. "Data Science and AI for Sustainable Futures: Opportunities and Challenges," Sustainability, MDPI, vol. 17(5), pages 1-20, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:2019-:d:1600480
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    References listed on IDEAS

    as
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    Cited by:

    1. Linhua Xia & Zhen Cao & Muhammad Bilawal Khaskheli, 2025. "How Digital Technology and Business Innovation Enhance Economic–Environmental Sustainability in Legal Organizations," Sustainability, MDPI, vol. 17(14), pages 1-21, July.

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