The Science Space of Artificial Intelligence Knowledge Production

Identifying interdisciplinary emergence in the science of science: combination of network analysis and BERTopic

“…This has important implications considering the importance of scientific forecasting for understanding and developing effective science, technology, and innovation (STI) policy initiatives that aim to support science and to predict innovation trajectories (Börner et al 2018). Essentially, innovative outcomes are frequently the result of converging technologies that often heavily depend on interdisciplinary scientific inputs (Kogler et al 2022). Thus, and perhaps not surprisingly, contemporary attempts to address and to meet global grand challenges are directed toward interdisciplinary research where a deep integration of disciplines that combine different types of scientific and technological paradigms in genomic/ biotechnology, nanotechnology, and information technology (e.g., blockchain, sensors, AI, and Big Data) are often believed to be the most promising avenues to pursue (Petersen et al 2021).…”