Using Artificial Intelligence in Science and Technology Policy Research: A Pilot

Based on paradigm theory and socio-technical systems theory, this project explores the possibilities and pathways for artificial-intelligence-empowered science and technology (S&T) policy research. We will apply machine learning, natural language processing, and generative AI technologies to Chinese S&T policy documents and related literature as the primary corpus. The S&T policy analysis will be conducted through an in-depth semantic analysis of policy texts and related literature, multi-level analysis of policy synergies, intelligent assessment of policy effects, and the integration and validation of research methods. Leveraging large language models such as DeepSeek and other open-source architectures, we will develop a set of key technological systems for S&T policy research. This will enable an in-depth analysis of the formulation, implementation, evaluation, and feedback mechanisms of S&T policies and reveal the trajectory of China’s S&T policy development, thereby generating theoretical, practical, and policy implications. Theoretically, this project aims to develop a conceptual model integrating paradigm theory and socio-technical systems theory and to establish an analytical framework for AI-empowered S&T policy research. Practically, the project focuses on identifying the main application scenarios of AI as a research tool in S&T policy analysis, while critically examining its advantages and limitations.