Defining medical liability when artificial intelligence is applied on diagnostic algorithms: a systematic review

Abstract

Artificial intelligence (AI) in medicine is an increasingly studied and widespread phenomenon, applied in multiple clinical settings. Alongside its many potential advantages, such as easing clinicians’ workload and improving diagnostic accuracy, the use of AI raises ethical and legal concerns, to which there is still no unanimous response. A systematic literature review on medical professional liability related to the use of AI-based diagnostic algorithms was conducted using the public electronic database PubMed selecting studies published from 2020 to 2023. The systematic review was performed according to 2020 PRISMA guidelines. The literature review highlights how the issue of liability in case of AI-related error and patient’s damage has received growing attention in recent years. The application of AI and diagnostic algorithm moreover raises questions about the risks of using unrepresentative populations during the development and about the completeness of information given to the patient. Concerns about the impact on the fiduciary relationship between physician and patient and on the subject of empathy have also been raised. The use of AI in medical field and the application of diagnostic algorithms introduced a revolution in the doctor–patient relationship resulting in multiple possible medico-legal consequences. The regulatory framework on medical liability when AI is applied is therefore inadequate and requires urgent intervention, as there is no single and specific regulation governing the liability of various parties involved in the AI supply chain, nor on end-users. Greater attention should be paid to inherent risk in AI and the consequent need for regulations regarding product safety as well as the maintenance of minimum safety standards through appropriate updates.

Liability of Health Professionals Using Sensors, Telemedicine and Artificial Intelligence for Remote Healthcare

“…Of course, if a patient takes part in a research protocol evaluating sensors or AI, ethical guidelines must be followed, and informed consent might need to be signed by the patients after ethical approval of the study by an ad hoc committee. It should be highlighted that in order to obtain an informed consent in the context of sensors and AI, patients should be sufficiently informed to “understand risk, benefits and limitations of sensors and AI software” to be able to give consent to their use [ 47 ].…”

“…For example, when it is used only as a decision support, the radiologist who makes the final determination would be the one bearing the liability risk. However, when the sensor/AI algorithm acts autonomously, it could be “considered analogous to an employee of a facility, its negligence could be attributed to its supervising radiologist or to the institution” [ 47 ]. Of course, similarly to the example provided just before in telemedicine, a radiologist would be held liable if he/she had the chance to review the report and to detect errors and thus, the patient’s injury might have been prevented.…”

Unveiling the Potential: A Comprehensive Review of Artificial Intelligence Applications in Ophthalmology and Future Prospects

“…Upholding ethical principles of transparency, accountability, and patient-centered care is essential. This ensures that the integration of AI in ophthalmology respects and protects patient privacy rights while harnessing the potential of data-driven innovations to improve clinical outcomes and quality of care [ 37 , 38 ]. Through proactive measures and adherence to ethical guidelines, healthcare professionals can navigate the complex landscape of AI-driven healthcare while prioritizing patient safety and well-being.…”

Artificial Intelligence and Forensic Genetics: Current Applications and Future Perspectives

“…Furthermore, other papers have focused on the application of AI for the definition of the post-mortem interval (PMI) [37]. Finally, in medico-legal sciences, AI could play a pivotal role in the management of medical liability [38,39].…”