Civil Liability of Physicians in Joint Clinical Decisions of Medical Staff and Artificial Intelligence
Subject Areas : Civil Law
Nasim Roshanfekr
1
,
yasaman yaghobi
2
,
Ambar Dwi Erawati
3
1 - Student of Master’s Degree in Private Law, Department of Law, Ahrar Institute of Higher Education, Rasht, Iran.
2 - Associate Professor of Educational Management, Department of Nursing, Shahid Beheshti School of Nursing and Midwifery, Guilan University of Medical Sciences, Rasht, Iran.
3 - Master of Science in Private Law, Department of Law, Faculty of Humanities, Widya Husada Semarang University, Semarang, Indonesia.
Keywords: Physician civil liability, medical artificial intelligence, joint clinical decision-making, fault, causal relationship, CDSS, producer liability., ,
Abstract :
The rapid expansion of artificial intelligence in clinical decision support systems (CDSS) has improved the efficiency of diagnosis and treatment; however, this interaction among physicians, medical staff, and machines challenges the traditional boundaries of civil liability. The purpose of this study is to explain the legal and jurisprudential foundations of physicians’ liability in the Iranian legal system in scenarios of joint human–artificial intelligence decision-making (Human–AI Joint Decisions) and to distinguish it from the liability of system producers. The research method is descriptive–analytical with an interdisciplinary approach, relying on the Civil Liability Act of 1960, Articles 495 to 497 of the Islamic Penal Code (Ta’zirat), and general theories of liability (fault and causation). The findings indicate that within the current structure of Iran’s healthcare system, the physician, as the “final decision-maker,” bears direct civil liability, even when the error arises from incomplete data or complex artificial intelligence algorithms. Nevertheless, the complexities of proving causation and the growing dependence on technological tools highlight the need to reconsider traditional liability regimes. By proposing a framework of risk-based liability for software producers and offering suggestions for legislative reforms to prevent errors caused by fully autonomous systems (Autonomous AI), this article seeks to maintain a balance between technological innovation and the assurance of patient safety.
1. Akhtandi, Z. (2021). An introduction to the challenges of artificial intelligence in the field of civil liability. Harvard University.
2. Alibi, M., Fallah, N., & Golehban, A. (2021). Civil liability resulting from violation of privacy rights: A comparative study in the legal systems of Iran and the United States. Health Law Journal in Health Studies. [In Persian]
3. Alimi, M., & Teimouri, A. (2022). A review of the ethical and legal implications of artificial intelligence applications in the healthcare system. Journal of Medical Ethics, 17(43), 1–11. [In Persian]
4. Aqa Amini Fashami, H., Hamidi, M., & Mansouri, S. J. (2024). A comparative legal study of artificial intelligence in supportive care in Islamic law and the comparative research of Western law. [In Persian]
5. Danaefar, Z., & Ardebili, H. (2024). An analytical perspective on the civil liability of physicians using artificial intelligence in medicine. Journal of Legal Studies, 18(59). [In Persian]
6. Faqihi, M., Bakhtiari, A., & Fazl, S. (2024). Iran's criminal policy approach towards the use of artificial intelligence in the health sector. Legal Journal of the Medical Council of the Islamic Republic of Iran, 24(3), 110–121. [In Persian]
7. Griffin, F. (2021). Artificial intelligence and liability in health care. Health Matrix, 31, 65.
8. Gurupur, V. P., & Shelleh, M. (2021). Machine learning analysis for data incompleteness (madi): Analyzing the data completeness of patient records using a random variable approach to predict the incompleteness of electronic health records. IEEE Access, 9, 95994-96001. [In Persian]
9. Holzinger, A., Langs, G., Denk, H., Zatloukal, K., & Müller, H. (2019). Causability and explainability of artificial intelligence in medicine. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(4), e1312.
10. Hosseini Maraghei, M. F. (1997). Direct causation (Mubashirat) and indirect causation (Tasbib) (Vol. 2). Islamic Publications Office. [In Persian]
11. Katouzian, N. (1995). Non-contractual obligations (Vol. 1). University of Tehran Press. [In Persian]
12. Katouzian, N., et al. (2019). Physicians' liability in medical errors. Journal of Medical Law and Medical Ethics, 11(4). [In Persian]
13. Khajeh, S. (2025). Legal and jurisprudential investigation of the causes exonerating physicians' liability in the Iranian legal system. National Conference on Modern Research in Humanities, Tehran. [In Persian]
14. Nikbakht Nasrabadi, M., Ali, M. F., & Mohammadreza (2024). Civil liability arising from the use of artificial intelligence in surgery: An interpretation of the concept of fault. Medical Law Journal, 18(59), 903–919. [In Persian]
15. Nikfar, N., & Ramazan-Arm, N. (2026). Investigating private law solutions for artificial intelligence. Journal of Public Law and Intellectual Property. [In Persian]
16. Rashvand-e Haqiqi, S. A., Ebadi, H., & Ali, H. (2024). Feasibility study of the use of artificial intelligence in judicial proceedings or the non-liability of doctors in AI implementation regarding privacy protection. Medical Law Journal, 19(60). [In Persian]
17. Safai, S. H., & Rahimi, H. (2016). Civil liability: Non-contractual obligations. Samt Publications. [In Persian]
18. Salimi Farad, S. M. (2024). Civil liability resulting from violation of the judge's sovereignty law in medical errors within the context of private law of artificial intelligence. Medical Law Journal, 204–214. [In Persian]
19. Sarkik, K., Mahmoudi, M., & Samadi, K. (2024). Artificial intelligence in medicine: Ethical evaluation, developments, and issues. Applied Ethics Studies, 80, 43–75. [In Persian]
20. Zakerinia, H. (2021). Civil liability of artificial intelligence in the law of European Union countries. University of Shiraz. [In Persian]
