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Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021 (2306.09145v1)

Published 15 Jun 2023 in cs.CY

Abstract: Analysing historical patterns of AI adoption can inform decisions about AI capability uplift, but research to date has provided a limited view of AI adoption across various fields of research. In this study we examine worldwide adoption of AI technology within 333 fields of research during 1960-2021. We do this by using bibliometric analysis with 137 million peer-reviewed publications captured in The Lens database. We define AI using a list of 214 phrases developed by expert working groups at the Organisation for Economic Cooperation and Development (OECD). We found that 3.1 million of the 137 million peer-reviewed research publications during the entire period were AI-related, with a surge in AI adoption across practically all research fields (physical science, natural science, life science, social science and the arts and humanities) in recent years. The diffusion of AI beyond computer science was early, rapid and widespread. In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to cover over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. We note AI has experienced boom-bust cycles historically: the AI "springs" and "winters". We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.

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Authors (5)
  1. Stefan Hajkowicz (2 papers)
  2. Conrad Sanderson (62 papers)
  3. Sarvnaz Karimi (17 papers)
  4. Alexandra Bratanova (1 paper)
  5. Claire Naughtin (1 paper)
Citations (34)

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