Value, Success, and Performance Measurements of Knowledge, Innovation and Entrepreneurial Systems
Permanent URI for this collectionhttps://hdl.handle.net/10125/107541
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Item type: Item , Knowledge Combination Analysis Reveals That Artificial Intelligence Research Is More Like "Normal Science" Than "Revolutionary Science"(2024-01-03) Wang, Jieshu; Maynard, Andrew; Lobo, José; Michael, Katina; Motsch, Sébastien; Strumsky, DeborahArtificial Intelligence (AI) research is intrinsically innovative and serves as a source of innovation for research and development in a variety of domains. There is an assumption that AI can be considered "revolutionary science" rather than "normal science." Using a dataset of nearly 300,000 AI publications, this paper examines the co-citation dynamics of AI research and investigates its trajectory from the perspective of knowledge creation as a combinatorial process. We found that while the number of AI publications grew significantly, they largely follows a normal science trajectory characterized by incremental and cumulative advancements. AI research that combines existing knowledge in highly conventional ways is a substantial driving force in AI and has the highest scientific impact. Radically new ideas are relatively rare. By offering insights into the co-citation dynamics of AI research, this work contributes to understanding its evolution and guiding future research directions.Item type: Item , Introduction to the Minitrack on Value, Success, and Performance Measurements of Knowledge, Innovation and Entrepreneurial Systems(2024-01-03) Smolnik, Stefan; Croasdell, Dave; Jennex, Murray