Assessing the research scene of green AI via bibliometric analysis.

Abdulmalik, Michael Rabiu; Ibeke, Ebuka; Ezenkwu, Chinedu Pascal; Iwendi, Celestine

Abstract

The environmental impact of artificial intelligence (AI) continues to rise as more people embrace the technology. The optimization of AI models to be more efficient, use less energy, and emit low carbon is essential. This bibliometric study presents an overview of literature published on Green AI research worldwide, with a particular focus on Africa. This study investigates the current state of research on Green AI, to learn about the most influential contributors, institutions, countries, journal outlets, and partnerships in Green AI research, and to assess their influence. Bibliometric information for the analysis was retrieved from the Web of Science database. Over 385 articles from 2016 to 2024 were obtained and analyzed with the aid of Microsoft Excel and VOSviewer, a bibliometric visualization network tool. The results showed that there has been a growth in Green AI research since the year 2020. A closer look at the data showed that the USA outperformed all other countries in terms of research output and collaboration. The dominant themes recorded in the study include energy efficiency, carbon footprint reduction, and the development of sustainable AI models. The results are noteworthy for the academic community because they provide current and emerging trends in Green AI research.

Citation

ABDULMALIK, M.R., IBEKE, E., EZENKWU, C.P. and IWENDI, C. [2024]. Assessing the research scene of green AI via bibliometric analysis. To be published in the Proceedings of the 2024 International conference on advances in communication technology and computer engineering (ICACTCE'24), 29-30 November 2024, Marrakech, Morocco. Lecture notes in networks and systems (LNNS). Cham: Springer [online], (accepted). To be made available from: https://www.springer.com/series/15179

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2024 International conference on advances in communication technology and computer engineering (ICACTCE'24)
• Start Date: Nov 29, 2024
• End Date: Nov 30, 2024
• Acceptance Date: Sep 5, 2024
• Deposit Date: Sep 6, 2024
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Series Title: Lecture notes in networks and systems (LNNS)
• Series ISSN: 2367-3370; 2367-3389
• Keywords: Artificial intelligence; Green AI; Sustainable AI; Environmental sustainability; Bibliometric analysis
• Public URL: https://rgu-repository.worktribe.com/output/2452142