Machine learning for sustainable development: leveraging technology for a greener future

Kagzi, Muneza and Khanra, Sayantan and Paul, Sanjoy Kumar (2023) Machine learning for sustainable development: leveraging technology for a greener future. Journal of Systems and Information Technology. pp. 1-40.

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Abstract

Purpose – From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries. Design/methodology/approach – This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development. Findings – ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals. Originality/value – This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence, Clean energy, Industry innovation, Learning algorithms, Responsible consumption, Smart cities
Divisions:	General Management and Enterpreneurship
Depositing User:	Mr. Mahesha Havanje
Date Deposited:	08 Nov 2023 06:02
Last Modified:	11 Mar 2024 09:54
URI:	http://tapmi.informaticsglobal.com/id/eprint/802

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