A bibliometric exploration of the intersection between artificial intelligence and social responsibility: evidence from scopus

Autores

  • Abdelwahab Boubaa
  • Bedj Bedj Toufik
  • Dhia Smaali

DOI:

https://doi.org/10.34140/bjbv6n4-060

Palavras-chave:

artificial intelligence, social responsibility, sustainability, artificial intelligence ethics, bibliometric analysis

Resumo

Purpose. This paper aims to explore the intersection between artificial intelligence (AI) and social responsibility (SR) through a bibliometric analysis of 779 peer-reviewed articles published from 2019 to 2023 in the Scopus database. The study employs tools such as R Studio (Bibliometrix) and VOSviewer to identify key trends, influential authors, and research clusters within this emerging field.

Results. The analysis reveals an annual research growth rate of 54.46%, with significant contributions from prominent authors like Gupta S, Kumar A, and Mehmood R, and institutions such as Kaunas University of Technology and Wuhan University. The keyword analysis highlights six main research clusters: the use of AI in resource management with a focus on "water" and "irrigation"; topics around "AI," "sustainability," "corporate SR," and "ethics"; applications in "policymaking" and "governance"; and research related to "energy" and "investments." Despite the rapid growth, significant gaps persist, including a lack of comprehensive frameworks to integrate AI with broader SR practices, as well as geographic disparities, with dominant contributions from countries like China, the USA, and the UK, while regions such as Africa and the Middle East remain underrepresented.

Scientific novelty. This study contributes to the field by identifying critical gaps in current research on AI and SR, particularly the absence of integrated frameworks that address ethical AI applications across multiple sectors. It also highlights the need for more geographically diverse studies and calls for a more interdisciplinary approach to responsibly align AI practices with SR goals.

Practical value. The findings underscore the importance of fostering AI research that is not only technologically advanced but also ethically grounded, especially in underrepresented regions. By addressing existing gaps and encouraging interdisciplinary research, this study advocates for the responsible development of AI to enhance SR practices globally, thus fostering a more equitable and sustainable future.

Referências

Aria, M., & Cuccurullo, C. (2017). bibliometrix : An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959‑975. https://doi.org/10.1016/j.joi.2017.08.007

Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities. Technological Forecasting and Social Change, 163, 120420. https://doi.org/10.1016/j.techfore.2020.120420

Baker, H. K., Kumar, S., & Pandey, N. (2021). Forty years of the Journal of Futures Markets : A bibliometric overview. Journal of Futures Markets, 41(7), 1027‑1054. https://doi.org/10.1002/fut.22211

Binns, R. (2017). Fairness in Machine Learning : Lessons from Political Philosophy. https://doi.org/10.48550/ARXIV.1712.03586

Camilleri, M. A. (2024). Artificial intelligence governance : Ethical considerations and implications for social responsibility. Expert Systems, 41(7). Scopus. https://doi.org/10.1111/exsy.13406

Carroll, A. B. (2021). Corporate Social Responsibility : Perspectives on the CSR Construct’s Development and Future. Business & Society, 60(6), 1258‑1278. https://doi.org/10.1177/00076503211001765

Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field : A practical application to the Fuzzy Sets Theory field. Journal of Informetrics, 5(1), 146‑166. https://doi.org/10.1016/j.joi.2010.10.002

Cowin, J., Leon, C., Brock, S., & Torres, X. O. (2024). AI and the future of marketing education through the lens of the space merchants. Brazilian Journal of Business, 6(2), e70382. https://doi.org/10.34140/bjbv6n2-024

Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective : A systematic literature review. Journal of Business Research, 121, 283‑314. https://doi.org/10.1016/j.jbusres.2020.08.019

Dignum, V. (2019). Responsible Artificial Intelligence : How to Develop and Use AI in a Responsible Way. Springer International Publishing. https://doi.org/10.1007/978-3-030-30371-6

Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis : An overview and guidelines. Journal of Business Research, 133, 285‑296. https://doi.org/10.1016/j.jbusres.2021.04.070

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An Ethical Framework for a Good AI Society : Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689‑707. https://doi.org/10.1007/s11023-018-9482-5

Hua, X., Hasan, N. A. M., De Costa, F., & Qiao, W. (2024). Opportunities or Challenges ? The Interplay between Artificial Intelligence and Corporate Social Responsibility Communication. Business Systems Research, 15(1), 131‑157. Scopus. https://doi.org/10.2478/bsrj-2024-0007

Khare, S., Uniyal, V., Kathuria, S., Chauhan, A. S., Akram, S. V., & Aluvala, S. (2024). Transformation of Corporate Social Responsibility Practices : Adapting Artificial Intelligence and Internet of Things. In Santosh K., Makkar A., Conway M., Singh A.K., Vacavant A., Abou el Kalam A., Bouguelia M., & Hegadi R. (Éds.), Commun. Comput. Info. Sci.: Vol. 2026 CCIS (p. 165‑177). Springer Science and Business Media Deutschland GmbH; Scopus. https://doi.org/10.1007/978-3-031-53082-1_14

Klerkx, L., & Rose, D. (2020). Dealing with the game-changing technologies of Agriculture 4.0 : How do we manage diversity and responsibility in food system transition pathways? Global Food Security, 24, 100347. https://doi.org/10.1016/j.gfs.2019.100347

Medaker, R. E., Loukil, S., & Mchich, R. (2024). Towards social responsibility 2.0 for Moroccan public establishments and enterprises : Artificial intelligence and new technologies at the service of sustainable development. Journal of Autonomous Intelligence, 7(3). https://doi.org/10.32629/jai.v7i3.1385

Morley, J., Floridi, L., Kinsey, L., & Elhalal, A. (2020). From What to How : An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices. Science and Engineering Ethics, 26(4), 2141‑2168. https://doi.org/10.1007/s11948-019-00165-5

Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability : Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104. https://doi.org/10.1016/j.ijinfomgt.2020.102104

Pai, V., Chandra, S., & SP Jain School of Global Management. (2022). Exploring Factors Influencing Organizational Adoption of Artificial Intelligence (AI) in Corporate Social Responsibility (CSR) Initiatives. Pacific Asia Journal of the Association for Information Systems, 14, 82‑115. https://doi.org/10.17705/1pais.14504

Rosemann, A., & Zhang, X. (2022). Exploring the social, ethical, legal, and responsibility dimensions of artificial intelligence for health – a new column in Intelligent Medicine. Intelligent Medicine, 2(2), 103‑109. https://doi.org/10.1016/j.imed.2021.12.002

Russell, S. J., & Norvig, P. (2021). Artificial intelligence : A modern approach (Fourth edition). Pearson.

Saveliev, A., & Zhurenkov, D. (2021). Artificial intelligence and social responsibility : The case of the artificial intelligence strategies in the United States, Russia, and China. Kybernetes, 50(3), 656‑675. Scopus. https://doi.org/10.1108/K-01-2020-0060

Vallor, S., & Ganesh, B. (2023). Artificial intelligence and the imperative of responsibility. In M. Kiener, The Routledge Handbook of Philosophy of Responsibility (1re éd., p. 395‑406). Routledge. https://doi.org/10.4324/9781003282242-43

Van Eck, N. J., & Waltman, L. (2010). Software survey : VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523‑538. https://doi.org/10.1007/s11192-009-0146-3

Wang, Q., & Su, M. (2020). Integrating blockchain technology into the energy sector—From theory of blockchain to research and application of energy blockchain. Computer Science Review, 37, 100275. https://doi.org/10.1016/j.cosrev.2020.100275

Wu, L., Chen, Z. F., & Tao, W. (2024). Instilling warmth in artificial intelligence ? Examining publics’ responses to AI-applied corporate ability and corporate social responsibility practices. Public Relations Review, 50(1). Scopus. https://doi.org/10.1016/j.pubrev.2024.102426

Zhao, W.-W. (2018). Improving Social Responsibility of Artificial Intelligence by Using ISO 26000. IOP Conf. Ser. Mater. Sci. Eng., 428(1). Scopus. https://doi.org/10.1088/1757-899X/428/1/012049

Zhao, W.-W. (2019). Research on social responsibility of artificial intelligence based on ISO 26000. In Wang J., Deng K., Patnaik S., & Yu Z. (Éds.), Adv. Intell. Sys. Comput. (Vol. 856, p. 130‑137). Springer Verlag; Scopus. https://doi.org/10.1007/978-3-030-00214-5_17

Downloads

Publicado

2024-12-11

Como Citar

Boubaa, A., Toufik, B. B., & Smaali, D. (2024). A bibliometric exploration of the intersection between artificial intelligence and social responsibility: evidence from scopus. Brazilian Journal of Business, 6(4), e75821. https://doi.org/10.34140/bjbv6n4-060

Edição

Seção

Artigos