生成式人工智能服务提供者能否适用避风港规则——基于侵权主体适格性的探讨
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浙江工商大学 法学院,浙江 杭州 310018

作者简介:

李晓阳,法学博士,浙江工商大学法学院(知识产权学院)特聘副教授。

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中图分类号:

D923.4

基金项目:

2024年度浙江省哲学社会科学规划课题“浙江省数据要素流通交易的法律规则研究”(24NDQN076YB)


Can generative AI service providers apply the safe harbor rules: an exploration based on the suitability of infringing subjects
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Law School, Zhejiang Gongshang University, Hangzhou 310018, P.R.China

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    摘要:

    生成式人工智能服务在内容生产中的深度参与,对原有的网络版权架构造成强烈冲击,生成式人工智能服务提供者的侵权责任分配成为亟待解决的难题。避风港规则作为过去网络时代平衡技术创新与版权保护的基石,当前面临着是否能适用于这一全新主体的严峻考验。文章基于侵权主体适格性的视角,对此展开讨论。从制度演进历史来看,避风港规则的适用高度依赖于主体的适格性,其经历了网络服务提供者与内容提供者分离,到内容服务提供者兴起的变化。然而,生成式人工智能技术实现了从“发现信息”向“重组信息”甚至“创造信息”的跨越。生成式人工智能服务提供者直接参与内容生产环节,打破了传统网络服务提供者不参与内容的“中立性”前提;同时,由于其内容生成受制于用户指示,且跨模态的规模化生产导致内容来源难以回溯。它也无法被归类为版权法意义上的内容提供者。因此,传统的“网络服务提供者与内容提供者”二元主体框架在生成式人工智能时代陷入适用迷思。如果强行将生成式人工智能服务提供者拟制为传统网络服务提供者,并径直适用现有的避风港规则,将使其陷入合规的“两难”困境:一方面,受限于生成式人工智能的创作工具本质,其无法履行防范侵权作品传播的“注意义务”;另一方面,由于AI生成内容是根据参数实时生成而非事先储存,服务提供者在技术上无法完成“通知—删除”规则下的断开链接或删除等必要措施。因此,破局点为摒弃修补式路径,在法律上承认生成式人工智能服务提供者是一类全新的独立责任主体。在其侵权责任的判断上,应当从传统避风港规则关注传播的“知情/不知情”推定,转向关注内容生成的“可知/不可知”标准。基于此,文章提出应当在当前内容生产者责任框架下,科学引入并重构专属于该类主体的“AI避风港”规则。具体包括:一是设立“AI训练免责”机制,明确将合法作品用于模型训练的技术处理行为视为非侵权使用;二是设立“可知免责”规则,要求提供者通过添加水印标识和提供来源检索链接,确保生成内容及来源处于“可知”状态,并以此作为责任划分与抗辩的依据;三是设立“绕行免责”规则,鼓励服务提供者通过模型优化、重写与安全评估,主动偏离训练数据以规避侵权风险。通过这一套全新规则的构建,旨在保障AIGC技术持续创新发展的同时,有效维持现有版权秩序的制度平衡。

    Abstract:

    The deep involvement of generative AI (GenAI) in content production has severely impacted the existing internet copyright legal framework, making the allocation of infringement liability for GenAI service providers a core challenge that urgently needs to be addressed. As the cornerstone of balancing technological innovation and copyright protection in the internet era, the safe harbor rules are currently facing a severe test regarding their applicability to this new subject. This paper conducts an in-depth exploration of this issue from the perspective of the suitability of infringing subjects.From the history of institutional evolution, the application of the safe harbor rules highly depends on the suitability of subjects, having undergone the separation of internet service providers (ISPs) and internet content providers (ICPs), as well as the rise of content service providers. However, GenAI technology has achieved a leap from discovering information to reorganizing information and even creating information. GenAI service providers directly participate in the content production process, breaking the neutrality premise of traditional ISPs that do not participate in content creation. Meanwhile, because its content generation is subject to user instructions, and the cross-modal, large-scale production makes it difficult to trace the source of the content, it cannot be classified as an ICP within the meaning of copyright law. Therefore, the traditional dual-subject framework of internet service providers and content providers has fallen into a dilemma of applicability in the GenAI era.If GenAI service providers are forcibly regarded as traditional ISPs and the existing safe harbor rules are directly applied, it will plunge them into a dilemma of compliance. On the one hand, constrained by the technological essence of GenAI as a pen rather than paper, it cannot fulfill the duty of care to prevent the dissemination of infringing works. On the other hand, since AI-generated content is generated in real-time based on parameters rather than stored in a database in advance, service providers are technically unable to take necessary measures such as disconnecting links or deleting content under the notice and takedown rules. Therefore, the key to breaking the deadlock lies in abandoning the patching approach and legally recognizing GenAI service providers as a brand-new, independent liable subject. In determining their infringement liability, the focus should shift from the traditional safe harbor rules’ presumption of actual knowledge (informed or not) regarding dissemination to the standard of knowability (knowable or not) regarding content generation.Based on this, this paper proposes that a new AI safe harbor rule exclusively tailored for such subjects should be scientifically introduced and reconstructed within the framework of content producer liability under the Interim Measures for the Management of Generative Artificial Intelligence Services. Specifically, it includes three core mechanisms: First, establishing an AI training exemption mechanism, explicitly treating the technical processing behavior of using lawful works for model training as non-infringing use. Second, establishing a knowable exemption rule, requiring providers to ensure that the generated content and its sources are in a knowable state by adding visible and invisible watermarks and providing source retrieval links, and using this as a basis for liability apportionment and defense. Third, establishing a circumvention exemption rule, encouraging service providers to proactively deviate from training data through model optimization, rewriting, and security assessments to evade infringement risks. The construction of this set of brand-new rules aims to effectively maintain the institutional balance of the existing copyright order while safeguarding the continuous innovative development of GenAI technology.

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李晓阳.生成式人工智能服务提供者能否适用避风港规则——基于侵权主体适格性的探讨[J].重庆大学学报社会科学版,2026,32(2):224-238. DOI:10.11835/j. issn.1008-5831. fx.2026.03.004

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  • 在线发布日期: 2026-05-27
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