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

Author

Listed:
  • Ding, Liangping
  • Lawson, Cornelia
  • Shapira, Philip

    (The University of Manchester)

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.

Suggested Citation

  • Ding, Liangping & Lawson, Cornelia & Shapira, Philip, 2025. "Tracking AI’s Scientific Anatomy: A Novel Framework for Analyzing the Use and Diffusion of AI in Science," SocArXiv 7ed2b_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:7ed2b_v1
    DOI: 10.31219/osf.io/7ed2b_v1
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    References listed on IDEAS

    as
    1. Chen, Jiyao & Shao, Diana & Fan, Shaokun, 2021. "Destabilization and consolidation: Conceptualizing, measuring, and validating the dual characteristics of technology," Research Policy, Elsevier, vol. 50(1).
    2. Strumsky, Deborah & Lobo, José, 2015. "Identifying the sources of technological novelty in the process of invention," Research Policy, Elsevier, vol. 44(8), pages 1445-1461.
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