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机器学习著作权法定许可的适用基础与规则构建

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人工智能模型训练(机器学习)侵权是人工智能著作权冲突中的重要问题.扩张适用合理使用制度和加强损害赔偿救济难以解决社会利益失衡的难题,法定许可模式仍具有难以替代的利益调和功能.机器学习法定许可的使用行为仅限于复制,商业性数据挖掘必须遵守法定许可,合理使用仅适用于公益性明显强于商业性的情形.法定许可费用的制定可以参考损害赔偿许可使用费的裁定方法,费用的收转仍需通过著作权集体管理组织配合执行,但是需要提高作品使用者的信息标注义务和完善人工智能法定许可信息机制.机器学习孤儿作品的特殊情形可以采用责任限制为主、法定许可为辅的二元治理模式.人工智能研发者负有数据过滤和信息披露的注意义务,后者应当遵循强制公开和公平合理原则;人工智能服务提供者则是在避风港规则的基础上,承担研发者信息披露的形式审查等义务.
Artificial intelligence model training(machine learning)infringement is an important issue that needs to be addressed urgently in AI-related copyright conflicts.Expanding fair use system and enhancing remedy of damages cannot effectively solve the problem of imbalance of social interests,while statutory licensing remains essential for reconciling these interests.Statutory licensing for machine learning shall be limited to copying,commercial data mining must comply with the statutory licensing,and fair use shall only apply to cases where public interest significantly outweighs commercial use.Statutory licensing fees can be set with reference to the method of determining royalties for damages,and its collection and allocation should still be carried out through copyright collective management organizations.It is necessary to improve the information labeling obligations of users,and to improve the statutory licensing information mechanism for AI.In the special case of orphan works for machine learning,the dual approach of liability limitation and statutory licensing could be adopted.AI developers have the duty of care for data filtering and information disclosure,the latter should follow the principles of mandatory disclosure and fairness and reasonableness;AI service providers,based on safe harbor rules,must undertake obligations,among others,the formal review of information disclosure by developers.

machine learningstatutory licensingsocial interestsorphan worksduty of care

蔡元臻

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同济大学法学院

机器学习 法定许可 社会利益 孤儿作品 注意义务

2024

知识产权
中国知识产权研究会

知识产权

CSSCICHSSCD北大核心
影响因子:1.115
ISSN:1003-0476
年,卷(期):2024.(11)