Civil liability for the actions of autonomous AI in healthcare: an invitation to further contemplation

Ahmed Eldakak (), Abdulla Alremeithi, Emad Dahiyat, Moatasem El-Gheriani, Hassan Mohamed and Mohammad Ibrahim Abdulrahim Abdulla
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Ahmed Eldakak: United Arab Emirates University
Abdulla Alremeithi: United Arab Emirates University
Emad Dahiyat: United Arab Emirates University
Moatasem El-Gheriani: United Arab Emirates University
Hassan Mohamed: United Arab Emirates University
Mohammad Ibrahim Abdulrahim Abdulla: United Arab Emirates University

Palgrave Communications, 2024, vol. 11, issue 1, 1-8

Abstract: Abstract There are already a number of autonomous robots that play a significant role in improving the quality of healthcare in different areas ranging from basic health diagnosis to complex surgeries. However, using robots and machine learning applications in the healthcare context poses concerns over liability for patient injury. This paper will thus attempt to investigate the potential legal problems that might arise if AI technology evolves or is commonly used in clinical practice. It also examines whether the traditional doctrines of liability can adequately address the liability for the injuries stemming from acts of autonomous robots. As such, this paper adopted both descriptive and analytical methodologies to explore the main focus of the study. while the descriptive methodology was used to spot light on various theories of liability, the analytical methodology was used to critically examine the main theories that have been advanced to deal with autonomous robots and predict the necessity of legal reform. Throughout this paper, the authors insist on the importance of distinguishing between robots in light of their degree of autonomy and then drafting liability rules depending on whether the action was done autonomously by an unattended robot or whether it was done automatically by an attended robot. Finally, the paper concludes with the proposal of a series of factors to be considered for the future regulation of AI Robots in the healthcare context.

Date: 2024
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DOI: 10.1057/s41599-024-02806-y

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