论DeepSeek类人工智能模型训练的著作权侵权责任认定

On the Determination of Copyright Infringement Liability for DeepSeek-like Artificial Intelligence Model Training

  • 摘要: 随着算法、算力与大数据技术的提高,DeepSeek类人工智能技术快速迭代发展。当前,DeepSeek类人工智能在提升经济社会效益的同时,也导致模型训练的著作权侵权频发。其中,在技术运行层,“收集—训练”逻辑结构引致作品训练使用失当;在侵权认定层,“接触+实质性相似”侵权认定标准适用失灵;在抗辩事由层,著作权合理使用规则适配失效。面对DeepSeek类人工智能模型训练的著作权侵权风险,应秉持促进人工智能创新发展的立场,采用“过错责任原则”认定著作权侵权责任。同时,优化著作权侵权认定标准,引入数据挖掘合理使用新类型,设置“新型避风港规则”鼓励商业性模型训练以恰当分配服务提供者责任,辅之以著作权侵权责任保险与赔付基金制度以分散著作权侵权风险,从而实现著作权侵权规制与促进DeepSeek类人工智能发展的平衡。

     

    Abstract: With the improvement of algorithms, arithmetic power and big data technology, DeepSeek-like artificial intelligence technology has developed rapidly and iteratively. Currently, DeepSeek-like artificial intelligence has triggered the copyright infringement of model training while enhancing economic and social benefits. Among them, in the technical operation layer, the logical structure of “collection-training” leads to the improper use of works training; in the infringement determination layer, the application of the infringement determination standard of “contact+substantial similarity” fails to work; in the defense layer, the fair use of copyright fails to apply. In the face of the copyright infringement risk of DeepSeek-like artificial intelligence model training, the principle of fault liability should be adopted to recognize copyright infringement liability in order to promote the innovative development of AI. At the same time, the copyright infringement determination standard should be optimized, new types of fair use of data mining should be introduced, “new safe harbor rule” to encourage commercial model training to appropriately allocate the responsibility of service providers should be set up, supplemented by copyright infringement liability insurance and compensation fund system to disperse the risk of copyright infringement, so as to achieve the goal of copyright infringement regulation and promote the development of DeepSeek-like artificial intelligence.

     

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