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Application of AI/ML techniques in achieving SDGs: a bibliometric study

Author

Listed:
  • A. Jiran Meitei

    (University of Delhi)

  • Pratibha Rai

    (University of Delhi)

  • S. S. Rajkishan

    (IILM University)

Abstract

This paper reviews the application of AI & ML techniques in achieving the UN Sustainable Development Goals, as documented in various studies during 2017–2022. A systematic bibliometric review of a sample of 250 peer-reviewed journal articles selected from two scientific databases, Scopus and Web of Science, was undertaken (i) to gauge the trend in publications on the application of specific innovative technologies, especially AI and ML, for achieving the SDGs; (ii) to analyze the blind spots of AI adversely affecting sustainability, which are derived from the literature review and to examine the solutions offered in the literature to counter the adverse effects of AI, and (iii) to gauge the future direction of research. The highest number of studies originated from China, the USA, Spain, the UK, and Australia. Evident collaborations between countries and universities are also discernible. The study identified the journals, Sustainability, Remote Sensing, IEEE Access, and Journal of Cleaner Production as core sources through Bradford’s law. The findings show that AI holds promise, but there is overexuberance about its positive outcome. The study shows a need to impose regulatory requirements and enforce regular verification to ensure that AI remains a subject of constant scrutiny for trust, transparency, and adherence to universal ethical standards for SDG achievement. The findings could also provide researchers with a direction for integrating AI/ML in achieving the SDGs.

Suggested Citation

  • A. Jiran Meitei & Pratibha Rai & S. S. Rajkishan, 2025. "Application of AI/ML techniques in achieving SDGs: a bibliometric study," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(1), pages 281-317, January.
    • Handle: RePEc:spr:endesu:v:27:y:2025:i:1:d:10.1007_s10668-023-03935-1
    DOI: 10.1007/s10668-023-03935-1
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    References listed on IDEAS

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