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

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.

Automated summary

This paper reviews the application of AI and ML techniques in achieving the UN Sustainable Development Goals based on studies from 2017 to 2022. The findings suggest that while AI holds promise, there is a tendency for overexuberance regarding its positive outcomes. The study emphasizes the need for regulatory requirements and regular verification to ensure that AI adheres to ethical standards for sustainable development.