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

Q2 Computer Science

Journal of Systems and Information Technology Pub Date : 2023-11-06 DOI:10.1108/jsit-11-2022-0266

Muneza Kagzi, Sayantan Khanra, Sanjoy Kumar Paul

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引用次数: 0

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.

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机器学习促进可持续发展:利用技术创造更绿色的未来

从技术决定论的角度来看，机器学习(ML)可能对可持续发展做出重大贡献。本研究的目的是综合先前关于机器学习在促进可持续性方面的作用的文献，并鼓励未来的研究。本研究对110篇论文进行了系统回顾，这些论文展示了机器学习在可持续发展背景下的应用。机器学习技术可以通过利用数据揭示模式和促进各种变量的预测，从而帮助决策过程，从而在实现可持续发展方面发挥至关重要的作用。通过对先前研究结果的综合，很明显，机器学习可能有助于实现联合国的许多可持续发展目标。原创性/价值本研究代表了对ML对可持续性贡献的文献进行全面检查的初步调查之一。分析表明，该研究领域仍处于早期阶段，需要进一步探索。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Systems and Information Technology Computer Science-Computer Science (all)

CiteScore

4.40

自引率

0.00%

发文量

期刊介绍： The Journal provides an avenue for scholarly work that researches systems thinking applications, information systems, electronic business, data analytics, information sciences, information management, business intelligence, and complex adaptive systems in the application domains of the business environment, health, the built environment, cultural settings, and the natural environment. Papers examine the wider implications of the systems or technology being researched. This means papers consider aspects such as social and organisational relevance, business value, cognitive implications, social implications, impact on individuals or community perspectives, and the development of solutions, rather than focusing solely on the technology. The Journal of Systems and Information Technology is open to a wide range of research methodologies and paper styles including case studies, surveys, experiments, review papers, design science, design thinking and both theoretical and methodological papers. The focus of the journal will be to publish work that fits into the following broad areas of research: Behavioural Information Systems and Human-Computer Interaction, Data Analytics, Data, Information and Security, E-Business, Intelligent Systems and Applications, Logistics and Supply Chain Management/Optimisation, Social Media Analysis, Technology Enhanced Learning.