Recently the set of knowledge referred to as “artificial intelligence” (AI), have become a mainstay of scientific research. AI techniques have not only greatly developed within their native areas of development but have also spread in terms of their application to multiple areas of science and technology. We conduct a large–scale analysis of AI in science. The first question we address is the composition of what is commonly labeled AI, and how the various sub-fields within this domain are linked together. We reconstruct the internal structure of the AI ecosystem through the co-occurrence of AI terms in publications, and we distinguish between 15 different specialities of AI. Further, we investigate the spreading of AI outside its native disciplines. We bring to light the dynamics of the diffusion of AI in the scientific ecosystem and we describe the disciplinary landscape of AI applications. Finally we analyze the role of collaborations for the interdisciplinary spreading of AI. While the study of science frequently emphasizes the openness of scientific communities, we show that collaborations between those scholars who primarily develop AI and those who apply it, are quite rare. Only a small group of researchers can gradually establish bridges between these communities.
