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From Bytes To Insights Through A Bibliometric Journey Into Ai'S Influence On Public Services

Author

Listed:
  • Ruxandra-Irina POPESCU

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Răzvan-Andrei CORBOȘ

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Ovidiu-Iulian BUNEA

    (Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

In the dynamic realm of public services, the integration of artificial intelligence (AI) has emerged as a transformative force, reshaping various sectors, including governance, urban development, healthcare, education, security infrastructure, decision-making processes, and responses to health crises. This article conducts an exploration spanning the years 1984 to 2023, employing bibliometric analysis to analyse global literature retrieved from the Scopus database. The central investigation revolves around the evolution of AI utilisation in public services during this period. Findings indicate a significant surge in AI-related publications, with notable global contributions from countries like China, India, and the United States, and a prevalence of computer science in AI research. Keyword clusters highlight seven prominent themes, ranging from digital governance to modelling health and social welfare in pandemics. Future research directions underscore ethical implications, AI adoption across government agencies, effectiveness in addressing urban challenges, machine learning applications in healthcare and education, security and privacy implications, application in diverse contexts, and AI's role in predicting and managing public health emergencies. This research contributes some necessary information for both academia and practical implementation in public services, laying the groundwork for future studies.

Suggested Citation

  • Ruxandra-Irina POPESCU & Răzvan-Andrei CORBOȘ & Ovidiu-Iulian BUNEA, 2023. "From Bytes To Insights Through A Bibliometric Journey Into Ai'S Influence On Public Services," APPLIED RESEARCH IN ADMINISTRATIVE SCIENCES, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 4(3), pages 4-18, December.
    • Handle: RePEc:rom:arasju:v:4:y:2023:i:3:p:4-18
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    References listed on IDEAS

    as
    1. Vetle I. Torvik & Marc Weeber & Don R. Swanson & Neil R. Smalheiser, 2005. "A probabilistic similarity metric for Medline records: A model for author name disambiguation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(2), pages 140-158, January.
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