The Expected Medical Liability as a result of the Health Sector’s Interaction with Artificial Intelligence – A Foresight-led, Analytical, and Comparative Study

The research focuses on medical liability in the context of AI. Considering that AI is a game-changer, it is a system that produces accurate outputs that may surpass doctors’ abilities. However, this technology is not risk-free. This puts doctors and hospitals in a complex situation regarding liability that arises from their interactions with AI. Therefore, it was necessary for the research to review medical legislation that preserves its traditional character in regulating medical liability, such as the Kuwaiti and American legislation. As well as to explore proposals that regulate AI and liability for the damage that results from the use of AI, such as the AI Act proposal and the AI liability directive proposal, which were both issued by the EU Commission.The research aims to highlight the deficiencies in the aforementioned legislation and proposals, and provide suitable rules regarding medical liability and AI. This research adopts foresight, analytical, and comparative approaches and has reached several results, the most important of which is that under current Kuwaiti and American legislations, doctors must apply the traditional standard of care, which does not include AI, to shield themselves from liability. The research also reached several recommendations, the most important of which is that physicians must have two standards of care in the EU, Kuwaiti, and American legislation. The first is the medical standard that obligates the use of AI, and the second is the AI user standard.

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Publication Details

Journal
International Review of Law
Published
2025-10-03
DOI
https://doi.org/10.29117/irl.2025.0336
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

The Expected Medical Liability as a result of the Health Sector’s Interaction with Artificial Intelligence – A Foresight-led, Analytical, and Comparative Study

Fahad Ahmad Almasoud
International Review of Law
Artificial Intelligence in Healthcare and Education
article

The Expected Medical Liability as a result of the Health Sector’s Interaction with Artificial Intelligence – A Foresight-led, Analytical, and Comparative Study

Fahad Ahmad Almasoud
article en

Abstract

The research focuses on medical liability in the context of AI. Considering that AI is a game-changer, it is a system that produces accurate outputs that may surpass doctors’ abilities. However, this technology is not risk-free. This puts doctors and hospitals in a complex situation regarding liability that arises from their interactions with AI. Therefore, it was necessary for the research to review medical legislation that preserves its traditional character in regulating medical liability, such as the Kuwaiti and American legislation. As well as to explore proposals that regulate AI and liability for the damage that results from the use of AI, such as the AI Act proposal and the AI liability directive proposal, which were both issued by the EU Commission.The research aims to highlight the deficiencies in the aforementioned legislation and proposals, and provide suitable rules regarding medical liability and AI. This research adopts foresight, analytical, and comparative approaches and has reached several results, the most important of which is that under current Kuwaiti and American legislations, doctors must apply the traditional standard of care, which does not include AI, to shield themselves from liability. The research also reached several recommendations, the most important of which is that physicians must have two standards of care in the EU, Kuwaiti, and American legislation. The first is the medical standard that obligates the use of AI, and the second is the AI user standard.

International Review of LawVol. 14(2)
Kuwait University (KW), Kuwait College of Science and Technology (KW)
Openalex Percentile: Top 80%
Artificial Intelligence in Healthcare and Education
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