THE SURGEON AND THE ALGORITHM: TRUST, AUTONOMY, AND RESPONSIBILITY IN AI-DRIVEN SURGICAL DECISION-MAKING — A SYSTEMATIC LITERATURE REVIEW

Jakub Marzec; Filip Kopacki; Daniel Jaskot; Weronika Szczeblewska; Jakub Świech; Marta Kamrowska; Katarzyna Apanasewicz; Natalia Kita; Natalia Sztenc; Patrycja Broniszewska

doi:10.31435/ijitss.2(50).2026.5510

Authors

Jakub Marzec University Clinical Hospital No. 1 of Pomeranian Medical University in Szczecin, Poland https://orcid.org/0009-0007-8336-7260
Filip Kopacki University Clinical Hospital No. 2, Pomeranian Medical University in Szczecin, Poland https://orcid.org/0009-0005-7897-8222
Daniel Jaskot Independent Public Provincial Integrated Hospital in Szczecin, Szczecin, Poland https://orcid.org/0009-0004-8678-9838
Weronika Szczeblewska Independent Public Provincial Integrated Hospital in Szczecin, Szczecin, Poland https://orcid.org/0009-0007-3956-622X
Jakub Świech University Clinical Hospital No. 2, Pomeranian Medical University in Szczecin, Poland https://orcid.org/0009-0001-1732-4162
Marta Kamrowska University Clinical Hospital No. 2, Pomeranian Medical University in Szczecin, Poland https://orcid.org/0009-0001-1570-0144
Katarzyna Apanasewicz J. Strus Multidisciplinary Municipal Hospital in Poznań, Poland https://orcid.org/0009-0001-0765-5398
Natalia Kita University Clinical Hospital No. 2, Pomeranian Medical University in Szczecin, Poland https://orcid.org/0009-0001-2277-6198
Natalia Sztenc Pomeranian Medical University, Szczecin, West Pomerania, Poland https://orcid.org/0009-0006-4307-7958
Patrycja Broniszewska University Clinical Hospital No. 2, Pomeranian Medical University in Szczecin, Poland https://orcid.org/0009-0000-6577-307X

DOI:

https://doi.org/10.31435/ijitss.2(50).2026.5510

Keywords:

Artificial Intelligence; Surgical Decision-Making; Trust in AI; Medical Ethics; Clinical Autonomy; Human–AI Interaction; Surgical Robotics

Abstract

The rapid integration of artificial intelligence (AI) into surgical practice is transforming clinical decision-making processes, raising critical questions regarding trust, autonomy, and responsibility in the operating room. This systematic literature review aims to synthesize current research on AI-driven surgical decision-making, with a particular focus on human–AI interaction and its ethical, cognitive, and legal implications.

The review was conducted in accordance with PRISMA guidelines. A comprehensive search of Scopus, Web of Science, PubMed, and Google Scholar identified a total of 312 records published between 2015 and 2025. After the removal of duplicates and screening based on predefined inclusion and exclusion criteria, 47 studies were included in the final analysis. These studies were categorized into three main thematic domains: trust in AI systems, autonomy and human oversight, and responsibility and accountability.

The findings indicate that AI technologies significantly enhance predictive accuracy, intraoperative support, and clinical decision-making efficiency (Gao et al., 2021; Shao et al., 2023). However, their increasing integration introduces challenges related to automation bias, reduced clinical autonomy, and ambiguity in legal responsibility ((O’Sullivan et al., 2019; Morris et al., 2023)). Trust in AI emerges as a multidimensional construct influenced by transparency, explainability, and user experience (Lopes et al., 2025).

The review highlights the need for improved explainability, standardized validation frameworks, and clearly defined accountability structures. It also identifies key gaps in the literature, particularly the lack of empirical studies on real-time human–AI decision-making and long-term impacts on surgical training. Future research should adopt interdisciplinary approaches to ensure the safe, ethical, and effective integration of AI into surgical practice.

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