Evolutionary stages and multidisciplinary nature of artificial intelligence research

Ricardo Arencibia-Jorge (), Rosa Lidia Vega-Almeida (), José Luis Jiménez-Andrade () and Humberto Carrillo-Calvet ()
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Ricardo Arencibia-Jorge: National Autonomous University of Mexico
Rosa Lidia Vega-Almeida: Empresa de Tecnologías de Información (ETI)
José Luis Jiménez-Andrade: National Autonomous University of Mexico
Humberto Carrillo-Calvet: National Autonomous University of Mexico

Scientometrics, 2022, vol. 127, issue 9, No 3, 5139-5158

Abstract: Abstract This paper analyzed the growth and multidisciplinary nature of Artificial Intelligence research during the last 60 years. Web of Science coverage since 1960 was considered, and a descriptive research was performed. A top-down approach using Web of Science subject categories as a proxy to measure multidisciplinarity was developed. Bibliometric indicators based on the core of subject categories involving articles and citing articles related to this area were applied. The data analysis within a historical and epistemological perspective allowed to identify three main evolutionary stages: an emergence period (1960–1979), based on foundational literature from 1950s; a re-emergence and consolidation period (1980–2009), involving a “paradigmatic” phase of development and first industrial approach; and a period of re-configuration of the discipline as a technoscience (2010–2019), where an explosion of solutions for productive systems, wide collaboration networks and multidisciplinary research projects were observed. The multidisciplinary dynamics of the field was analyzed using a Thematic Dispersion Index. This indicator clearly described the transition from the consolidation stage to the re-configuration of the field, finding application in a wide diversity of scientific and technological domains. The results demonstrated that epistemic changes and qualitative leaps in Artificial Intelligence research have been associated to variations in multidisciplinarity patterns.

Keywords: Artificial intelligence; Scientific production; Multidisciplinarity; Bibliometric indicators; Thematic dispersion index (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11192-022-04477-5

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