Evolutionary stages and multidisciplinary nature of artificial intelligence research

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 mul...

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Bibliographic Details
Published in:Scientometrics 2022-09, Vol.127 (9), p.5139-5158
Main Authors: Arencibia-Jorge, Ricardo, Vega-Almeida, Rosa Lidia, Jiménez-Andrade, José Luis, Carrillo-Calvet, Humberto
Format: Article
Language:English
Subjects:
Artificial intelligence
Bibliometrics
Computer Science
Configurations
Consolidation
Data analysis
Descriptive research
Epistemology
Information Storage and Retrieval
Library Science
Multidisciplinary research
Research projects
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Summary: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.
ISSN:0138-9130
1588-2861
DOI:10.1007/s11192-022-04477-5