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人工智能医疗侵权纠纷中的责任承担与举证分配

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涉及人工智能医疗技术的民事医疗纠纷中的侵权责任与举证分配已成为愈发重要的法学课题.不同国家对于人工智能侵权责任的分配机制是不同的.在我国,人工智能医疗侵权责任具有医疗损害责任与产品责任两种属性.根据实体法上的法律要件分类进行举证责任的分配是民事案件的一般规则.鉴于人工智能医疗存在技术上的特殊性与证据偏在的情形,有必要对其适用危险领域理论的举证责任分配规则.法院需要在人工智能医疗纠纷中根据具体情形进行举证责任的倒置与举证责任的减轻;同时,法院也可依当事人申请进行证据调查活动,通过文书提出命令等手段平衡双方当事人的证据收集能力.
Liability and Proof Allocation in Artificial Intelligence Medical Infringement Disputes
Infringement liability and proof allocation in civil medical disputes related to artificial intelli-gence(AI)medical technology has become an increasingly important legal topic.Different countries have different distribution mechanisms of AI infringement liability.In China,AI medical infringement li-ability has two attributes:medical damage liability and product liability.It is a general rule in civil cases to allocate the burden of proof according to the classification of legal elements in substantive law.Howev-er,in view of the technical particularity and partial evidence in AI medical treatment,it is necessary to apply the burden of proof allocation rule in the theory of dangerous domain.The court needs to reverse and/or reduce the burden of proof in AI medical disputes according to specific circumstances;in the mean time,the court can also investigate evidence according to the application of the parties involved,and balance the evidence collection ability of both parties through issuing orders in documents.

artificial intelligence(AI)medical disputeproduct liabilitymedical damage liabilityburden of proofthe theory of dangerous domain

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中国人民大学法学院,北京 100872

人工智能 医疗纠纷 产品责任 医疗损害责任 举证责任 危险领域理论

2024

太原理工大学学报(社会科学版)
太原理工大学

太原理工大学学报(社会科学版)

CHSSCD
影响因子:0.218
ISSN:1009-5837
年,卷(期):2024.42(1)
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