Research on the System Perfection of Medical Artificial Intelligence Damage Liability

DOI

10.2991/978-2-38476-511-9_99How to use a DOI?

Keywords

Medical artificial intelligence; Liability for damage; Causality

Abstract

With the rapid advancement of AI, its application in the medical field is becoming increasingly widespread, significantly enhancing the efficiency and quality of healthcare services. However, this widespread adoption also introduces a series of legal risks and challenges in attributing liability, particularly when AI technology causes potential or actual harm. Defining the legal responsibility of relevant parties becomes difficult under such circumstances.

Traditional medical damage liability focuses on the subjective fault of medical staff and the direct causal link between their actions and the resulting harm. In contrast, liability for damage caused by medical AI faces unique challenges. These include the opacity of algorithmic decision-making, uncertainty in causality due to technical complexity, and the diversification of responsible entities. These differences lead to a more complicated process for identifying liability and assigning blame, creating an urgent need for legal adaptation.

Given the particularity and complexity of medical AI damage liability, it is necessary to improve the legal regulatory framework at the legislative level. This involves clarifying the legal status and responsibilities of AI systems. Furthermore, strict industry standards and supervisory measures must be formulated to enhance the safety and reliability of medical AI products. To address the difficulties in establishing causation and the blurred boundaries of fault, it is crucial to define the subject qualification for liability and explore the establishment of specialized AI appraisal institutions. This would improve the transparency and certainty in determining causal relationships for such incidents.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Chenxiao Wei
PY  - 2025
DA  - 2025/12/31
TI  - Research on the System Perfection of Medical Artificial Intelligence Damage Liability
BT  - Proceedings of the 7th International Conference on Literature, Art and Human Development (ICLAHD 2025)
PB  - Atlantis Press
SP  - 851
EP  - 857
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-511-9_99
DO  - 10.2991/978-2-38476-511-9_99
ID  - Wei2025
ER  -