Application of AI/ML Techniques in Achieving SDGs: A Bibliometric Study

Abstract

Based on research conducted between 2017 and 2022, this article summarizes the ways in which artificial intelligence and machine
learning were used to accomplish the United Nations Sustainable Development Goals. Using Scopus and Web of Science,
researchers conducted a systematic bibliometric review of 250 peer-reviewed journal articles. The goals of the review were
threefold: (i) to identify current trends in publications about the use of innovative technologies like AI and ML to achieve the
SDGs; (ii) to identify areas where AI is having a negative impact on sustainability; and (iii) to determine where research should
go from here. China, the United States, Spain, the United Kingdom, and Australia were the top five countries from which research
were sourced. Cooperation between nations and educational institutions is also clearly visible. Using Bradford’s rule, the
analysis determined that the journals Sustainability, Remote Sensing, IEEE Access, and Journal of Cleaner Production were the
primary sources. Researchers have shown that AI has potential, but they worry that people are becoming too optimistic about
its benefits. The report highlights the need of regulating AI and conducting frequent verification to maintain confidence, transparency,
and adherence to universal ethical norms in order to fulfill the SDGs. The results may help point academics in the right
direction about how to use AI and ML to accomplish the SDGs.