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Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda

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  • Nishant, Rohit
  • Kennedy, Mike
  • Corbett, Jacqueline

Abstract

Artificial intelligence (AI) will transform business practices and industries and has the potential to address major societal problems, including sustainability. Degradation of the natural environment and the climate crisis are exceedingly complex phenomena requiring the most advanced and innovative solutions. Aiming to spur groundbreaking research and practical solutions of AI for environmental sustainability, we argue that AI can support the derivation of culturally appropriate organizational processes and individual practices to reduce the natural resource and energy intensity of human activities. The true value of AI will not be in how it enables society to reduce its energy, water, and land use intensities, but rather, at a higher level, how it facilitates and fosters environmental governance. A comprehensive review of the literature indicates that research regarding AI for sustainability is challenged by (1) overreliance on historical data in machine learning models, (2) uncertain human behavioral responses to AI-based interventions, (3) increased cybersecurity risks, (4) adverse impacts of AI applications, and (5) difficulties in measuring effects of intervention strategies. The review indicates that future studies of AI for sustainability should incorporate (1) multilevel views, (2) systems dynamics approaches, (3) design thinking, (4) psychological and sociological considerations, and (5) economic value considerations to show how AI can deliver immediate solutions without introducing long-term threats to environmental sustainability.

Suggested Citation

  • Nishant, Rohit & Kennedy, Mike & Corbett, Jacqueline, 2020. "Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda," International Journal of Information Management, Elsevier, vol. 53(C).
    • Handle: RePEc:eee:ininma:v:53:y:2020:i:c:s0268401220300967
    DOI: 10.1016/j.ijinfomgt.2020.102104
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    Citations

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    Cited by:

    1. Nassiri-Mofakham, Faria & Huhns, Michael N., 2023. "Role of culture in water resources management via sustainable social automated negotiation," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    2. Kumar, Sourabh & Kumar Barua, Mukesh, 2022. "Modeling and investigating the interaction among risk factors of the sustainable petroleum supply chain," Resources Policy, Elsevier, vol. 79(C).
    3. Abou-Foul, Mohamad & Ruiz-Alba, Jose L. & López-Tenorio, Pablo J., 2023. "The impact of artificial intelligence capabilities on servitization: The moderating role of absorptive capacity-A dynamic capabilities perspective," Journal of Business Research, Elsevier, vol. 157(C).
    4. Sjödin, David & Parida, Vinit & Kohtamäki, Marko, 2023. "Artificial intelligence enabling circular business model innovation in digital servitization: Conceptualizing dynamic capabilities, AI capacities, business models and effects," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    5. Dmitry A. Ruban, 2022. "Analytical Review of Conjugation of the Ethical Bases of Artificial Intelligence Implementation and Ecologization in Corporate Governance," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 21(2), pages 390-418.
    6. Purvis, Ben & Genovese, Andrea, 2023. "Better or different? A reflection on the suitability of indicator methods for a just transition to a circular economy," Ecological Economics, Elsevier, vol. 212(C).
    7. Leal Filho, Walter & Wall, Tony & Rui Mucova, Serafino Afonso & Nagy, Gustavo J. & Balogun, Abdul-Lateef & Luetz, Johannes M. & Ng, Artie W. & Kovaleva, Marina & Safiul Azam, Fardous Mohammad & Alves,, 2022. "Deploying artificial intelligence for climate change adaptation," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    8. Jean-Philippe Deranty & Thomas Corbin, 2022. "Artificial Intelligence and work: a critical review of recent research from the social sciences," Papers 2204.00419, arXiv.org.
    9. Abdelhamid Zaidi & Samuel-Soma M. Ajibade & Majd Musa & Festus Victor Bekun, 2023. "New Insights into the Research Landscape on the Application of Artificial Intelligence in Sustainable Smart Cities: A Bibliometric Mapping and Network Analysis Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 287-299, July.
    10. Mohammad I. Merhi, 2023. "An Assessment of the Barriers Impacting Responsible Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(3), pages 1147-1160, June.
    11. Manjul Gupta & Carlos M. Parra & Denis Dennehy, 2022. "Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter?," Information Systems Frontiers, Springer, vol. 24(5), pages 1465-1481, October.
    12. Wolfgang Ketter & Karsten Schroer & Konstantina Valogianni, 2023. "Information Systems Research for Smart Sustainable Mobility: A Framework and Call for Action," Information Systems Research, INFORMS, vol. 34(3), pages 1045-1065, September.
    13. Issa Helmi & Lakkis Hussein & Dakroub Roy & Jaber Jad, 2023. "Examining User Engagement and Experience in Agritech," International Journal of Contemporary Management, Sciendo, vol. 59(2), pages 17-32, June.
    14. Noura Metawa & Rhada Boujlil & Saad Alsunbul, 2023. "Fraud-Free Green Finance: Using Deep Learning to Preserve the Integrity of Financial Statements for Enhanced Capital Market Sustainability," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 610-617, November.
    15. Tae Wan Kim & Fabrizio Maimone & Katherina Pattit & Alejo José Sison & Benito Teehankee, 2021. "Master and Slave: the Dialectic of Human-Artificial Intelligence Engagement," Humanistic Management Journal, Springer, vol. 6(3), pages 355-371, December.
    16. Gupta, Brij B. & Gaurav, Akshat & Panigrahi, Prabin Kumar & Arya, Varsha, 2023. "Analysis of artificial intelligence-based technologies and approaches on sustainable entrepreneurship," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    17. Franco Donati & Sébastien M. R. Dente & Chen Li & Xaysackda Vilaysouk & Andreas Froemelt & Rohit Nishant & Gang Liu & Arnold Tukker & Seiji Hashimoto, 2022. "The future of artificial intelligence in the context of industrial ecology," Journal of Industrial Ecology, Yale University, vol. 26(4), pages 1175-1181, August.
    18. Mohammadreza Akbari & John L. Hopkins, 2022. "Digital technologies as enablers of supply chain sustainability in an emerging economy," Operations Management Research, Springer, vol. 15(3), pages 689-710, December.

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