Litcius/Paper detail

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

Muneza Kagzi, Sayantan Khanra, Sanjoy Kumar Paul

2023Journal of Systems and Information Technology13 citationsDOI

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.

Topics & Concepts

SustainabilitySustainable developmentOriginalityContext (archaeology)Computer scienceKnowledge managementDomain (mathematical analysis)Perspective (graphical)Process managementManagement scienceValue (mathematics)Engineering ethicsBusinessArtificial intelligencePolitical scienceEngineeringMachine learningCreativityPaleontologyBiologyMathematical analysisEcologyMathematicsLawGreen IT and SustainabilitySmart Cities and TechnologiesSustainable Supply Chain Management