Ethics and trustworthiness of artificial intelligence in Hepato-Pancreato-Biliary surgery: a snapshot of insights from the European-African Hepato-Pancreato-Biliary Association (E-AHPBA) survey

Niki Rashidian*, Mohammed Abu Hilal, Isabella Frigerio, Martina Guerra, Sigrid Sterckx, Francesca Tozzi, Giulia Capelli, Daunia Verdi, Gaya Spolverato, Aiste Gulla, Francesca Ratti, Andrew J. Healey, Alessandro Esposito, Matteo De Pastena, Andrea Belli, Stefan A. Bouwense, Angelakoudis Apostolos, Sven A. Lang, Victor López-López, Gregor A. StavrouLuca Aldrighetti, Oliver Strobel, Roland Croner, Andrew A. Gumbs*, E-AHPBA Innovation Committee

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background: Hepato-Pancreato-Biliary (HPB) surgery is a complex specialty and Artificial Intelligence (AI) applications have the potential to improve pre- intra- and postoperative outcomes of HPB surgery. While ethics guidelines have been developed for the use of AI in clinical surgery, the ethical implications and reliability of AI in HPB surgery remain specifically unexplored. Methods: An online survey was developed by the Innovation Committee of the E-AHPBA to investigate the current perspectives on the ethical principles and trustworthiness of AI in HPB Surgery among E-AHPBA membership. The survey consisted of 22 questions, based on guidelines outlined by the Artificial Intelligence Surgery Journal Task Force on AI Ethics in clinical surgery and was disseminated via email to all E-AHPBA members. Results: A total of 84 members of the E-AHPBA participated in the survey. Seventeen out of 22 questions achieved more than 80 % agreement, with nine of those exceeding 90 %. Five questions had agreement levels between 70 % and 80 %. Conclusion: While HPB surgeons are aware of the need to regulate the use of AI devices, robots, and to protect patient data, consensus appears to be heterogeneous regarding AI's role in mitigating gender-related and minority biases, as well as ensuring fairness and equity.
Original languageEnglish
Pages (from-to)502-510
Number of pages9
JournalHPB
Volume27
Issue number4
Early online date1 Jan 2025
DOIs
Publication statusPublished - Apr 2025

Keywords

  • LANGUAGE MODELS
  • HEALTH-CARE
  • PERFORMANCE
  • MEDICINE

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