With the rapid development of artificial intelligence, a new research paradigm, "Artificial Intelligence for Science (AI4S)," has emerged and is reshaping the fundamental logic of scientific research. Exploring the impact of AI4S on research in the field of scientific and technical information and its response mechanisms will help provide theoretical support and guidance for the future development of scientific and technical information science. This article reviews the landscape of scientific and technical information research in the AI4S era, conducts topic identification and evolution analysis based on BerTopic and LLM, and summarizes the responsiveness and limitations of scientific and technical information research to AI4S. Furthermore, it discusses the paradigm shift and problem reconstruction in the field of scientific and technical information under the influence of AI4S. A new paradigm for scientific and technical information research in the AI4S era is proposed from the perspectives of theoretical logic, research objects, research perspectives, and functional positioning. Moreover, the shift of research problems is analyzed with respect to traditional and new research tasks in the field of scientific and technological information. The study finds that current research in the field of scientific and technical information focuses more on "leveraging readily available data intelligence to greatly facilitate intelligent information." Future research should explore information-based intelligence in -depth, fully leveraging the leading role of scientific and technical information.
Cao Shujin Cao Ruye
. Research Landscape and Paradigm Reshaping in the Field of Scientific and Technological Information in the AI4S Era[J]. Library & Information, 2025
, 45(04)
: 49
-60
.
DOI: 10.11968/tsyqb.1003-6938.2025045
