AI of the Beholder: How Surgical and Medical Specialties View Intelligent Technology.

Journal: Surgical innovation
Published Date: Jan 13, 2026

Abstract

BackgroundHow clinicians conceptualize artificial intelligence reveals underlying assumptions about professional authority and decision-making. This study examined whether surgical and medical specialties frame AI differently in research and if such differences reflect divergent professional norms.Methods1561 AI-related research abstracts published between January 1, 2019, and March 27, 2025, in 30 high-impact journals. Abstracts were identified through a structured PubMed query and analyzed using a large language model (DeepSeek Reasoner) trained to classify along three dimensions: the human-AI relationship, the impact on professional autonomy, and the locus of decision control. A stratified validation sample was independently coded by a human rater. Chi-square testing and logistic regression were used to assess differences by specialty and publication year.ResultsSurgical abstracts more frequently framed AI as assistive (69.8% vs 54.9%; P < .001), explicitly addressed professional autonomy (73.5% vs 61.3%; P < .001), and specified decision control (69.3% vs 58.6%; P < .001) compared to medical abstracts. These differences persisted across the 7-year period. In multivariable logistic regression, assistive framing (OR, 2.43; 95% CI, 1.82-3.23) and explicit autonomy discussion (OR, 1.46; 95% CI, 1.11-1.92) were independently associated with surgical specialty.ConclusionsSurgical and medical specialties exhibit distinct patterns in how they conceptualize AI, reflecting established perspectives on authority, expertise, and the human-machine relationship. These framings have implications for AI tool design, clinical implementation, and healthcare governance. Recognizing conceptual differences on AI is critical as healthcare transitions toward algorithmically mediated decision-making, as they may shape the future culture of clinical care.

Authors

  • Daniel Schneider
    Diagnostic and Interventional Radiology, University Hospital Ulm, Germany.
  • Ethan D L Brown
    Neurological Surgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, USA.
  • Timothy G White
    Department of Neurosurgery, Northwell, Manhasset, NY, USA.
  • Jung Park
    Department of Neurosurgery, Northwell, Manhasset, NY, USA.
  • Max Ward
    Neurological Surgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, USA.
  • Aladine A Elsamadicy
    Department of Neurosurgery, Yale University School of Medicine, New Haven, CT.
  • Daniel M Sciubba
    Department of Neurosurgery, The Johns Hopkins Hospital, 600 North Wolfe Street; Meyer Building, Room 7-109, Baltimore, MD 21287, USA. Electronic address: [email protected].
  • Sheng-Fu Larry Lo
    Department of Neurosurgery, Northwell, Manhasset, NY, USA.

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