Artificial intelligence for science – adoption trends and future development pathways

Stefan Hajkowicz, Claire Naughtin, Conrad Sanderson, Emma Schleiger, Sarvnaz Karimi, Alexandra Bratanova and Tomasz Bednarz

MPRA Paper from University Library of Munich, Germany

Abstract: This paper aims to inform researchers and research organisations within the spheres of government, industry, community and academia seeking to develop improved AI capabilities. The paper is focused on the use of AI for science, and it describes AI adoption trends in the physical, natural and social science fields. Using a bibliometric analysis of peer-reviewed publishing trends over 63 years (1960–2022), the paper demonstrates a surge in AI adoption across all fields over the past several years. The paper examines future development pathways and explores implications for science organisations.

Keywords: Artificial intelligence; machine learning; science; AI capabilities; bibliometric analysis; Australia (search for similar items in EconPapers)
JEL-codes: O32 O33 O38 (search for similar items in EconPapers)
Date: 2022-11
New Economics Papers: this item is included in nep-ain and nep-cmp
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:115464

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