Tracking AI’s Scientific Anatomy: A Novel Framework for Analyzing the Use and Diffusion of AI in Science

Liangping Ding, Cornelia Lawson and Philip Shapira
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Philip Shapira: The University of Manchester

No 7ed2b_v1, SocArXiv from Center for Open Science

Abstract: Artificial intelligence (AI) promises to transform science by accelerating knowledge discovery, automating processes, and introducing new paradigms for research. However, there remains a limited understanding of how AI is being utilized in scientific research. In this paper, we develop a framework based on GPT-4 and SciBERT to identify AI’s role in scientific papers, differentiating between Foundational, Adaptation, Tool and Discussion modes of AI research. This allows us to capture AI’s diverse contributions, from theoretical advances to practical applications and critical analysis. We examine AI’s trajectory across these modes by analyzing time series, field-specific, and country trends. This approach expands on search-term based identification of AI contributions and offers insights into how AI is being deployed in science.

Date: 2025-11-02
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:7ed2b_v1

DOI: 10.31219/osf.io/7ed2b_v1

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