CHINA Law and Practice Contributed by: Gil Zhang, Diana Li, Muran Sun and Yongqi Tao, Fangda Partners
4. Liability and Risk in Healthcare AI 4.1 Liability Framework China has not yet established a dedicated legal framework specifically addressing liability allocation between AI-related stakeholders. Liabilities are allo - cated under the traditional tort law, contract law and administrative regulations regarding generic products, medical devices, patients and healthcare providers. The applicable legal framework governing the liability of healthcare AI systems is as follows. The Civil Code – Generic or Special Product Liability Provisions If a healthcare AI system causes personal injury or property damage due to defects, the liability depends on the system type. • If the healthcare AI system qualifies as a “generic product” (which is highly likely as PRC law defines “products” mainly by their sales purpose, without requiring physical/tangible form), the patients may claim product liability against the system’s pro - ducer/manufacturer (developer) and seller. A seller who compensates patients has the right to seek recourse from producers/manufacturers (develop - ers). A medical institution, as the direct user of the AI system, is generally not liable under product liability unless it caused the defect. • If the healthcare AI system is further classified as a “medical device”, then the patient can claim medi - cal damage liability not only against the producer/ manufacturer (developer) and the seller, but also directly against the medical institution in the first instance. The institution can then seek recourse from the producer/manufacturer (developer). Steps to determine whether the AI system is defective in judicial practice typically include the following. • Verifying that the AI system’s design complies with mandatory or recommended standards; violation of standards indicates defects. • If no standards are violated, examining the algo - rithmic logic to see if obvious improvements could have prevented the harm. If so, a defect might be recognised (currently, AI diagnosis is not yet a “black box”, meaning that the underlying algorith -
mic logic can always be examined). Additionally, the producer (developer) failing to provide neces - sary warnings to the user or patient may constitute a warning defect. Product Quality Law and Consumer Rights Protection Law If healthcare AI systems are defined as “products”, their safety, suitability and instructions must comply with relevant standards. Developers and sellers bear civil and administrative liability for non-compliance. Regulations on the Supervision and Administration of Medical Devices (2024 Revision) If healthcare AI systems qualify as medical devices, manufacturers are responsible for their quality, safety and effectiveness. Regulatory authorities may order recalls or impose penalties for design defects or soft - ware update failures. 4.2 Patient Harm and Malpractice Medical institutions and HCPs remain subject to tradi - tional medical malpractice standards. Given that most AI systems in clinical practice function as decision- support tools rather than fully autonomous systems, ultimate responsibility typically rests with the human user. Improper reliance on AI-generated recommen - dations or inadequate supervision of the system’s application can expose medical treatment providers to legal claims. In such cases, traditional rules on patient harm and malpractice apply, so medical institutions will be held liable only if their personnel are proven to be at fault and the cause of patient harm during diagnosis or treatment. Specifically, the patient must prove four elements: wrongful act, damage, causation and fault, where proving fault of medical personnel is the most challenging. 4.3 Risk Management Requirements China has not yet prescribed a unified risk manage - ment framework specific to healthcare AI, but medical institutions and developers are subject to some frag - mented regulatory and technical requirements.
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