人工智能训练数据池中的ODbL协议合规性研究

Research on ODbL Protocol Compliance in AI Training Data Pool

摘要: 开源协议是开源大模型生态治理中的关键要素，对其认识不足、履行不当既可能引发知识产权侵权风险，也可能陷入投入产出失衡的“合规陷阱”，亟需合规指引。随着人工智能技术的飞速发展，高质量、大规模的训练数据成为核心竞争力。数据池作为汇聚多源数据的重要载体，其构建与使用过程中的法律合规性问题日益凸显。开放数据库许可协议(ODbL)作为一种“著佐权”式的数据许可协议，旨在确保数据的共享与后续使用的开放性，其在人工智能数据领域的应用引发了新的法律挑战。

Abstract: Open-source licenses are a critical element in the governance of the open-source large model ecosystem. Insufficient understanding or improper implementation of these licenses can not only lead to intellectual property infringement risks but may also result in a “compliance trap” where input and output are unbalanced, creating an urgent need for compliance guidance. With the rapid advancement of artificial intelligence technology, high-quality, large-scale training data has become a core competitiveness. Data pools, as important carriers for aggregating multi-source data, increasingly face prominent legal compliance issues in their construction and usage. The Open Database License (ODbL), as a “copyleft” style data license agreement, aims to ensure the openness of data sharing and subsequent use. Its application in the field of artificial intelligence data has sparked new legal challenges.