兰台世界

本文基于“技术赋能—价值转化—风险治理”的分析框架，系统阐释生成式AI驱动档案数据要素化的内在机理，重点剖析数据治理、技术适配、伦理合规三大核心困境，并结合《中华人民共和国档案法实施条例》要求与行业实践案例，构建“技术—制度—伦理”三位一体的治理体系。研究发现，生成式AI可通过多模态语义解析、动态知识图谱构建、智能价值挖掘三重路径激活档案价值，而解决大模型“幻觉”、数据安全与权益界定问题是实现要素化落地的关键。

This paper systematically elucidates the intrinsic mechanism of generative AI-driven archival data factorization within the analytical framework of "technological empowerment-value transformation-risk governance". It focuses on dissecting three core challenges of data governance, technological adaptation, and ethical compliance, and proposes a "technology-institution-ethics" trinity governance system based on the requirements of the Regulations on the Implementation of the Archives Law and industry practice cases. Research findings reveal that generative AI can activate archival value through three pathways: multimodal semantic parsing, dynamic knowledge graph construction, and intelligent value mining. Addressing issues such as large model "hallucination", data security, and rights and interests delineation are pivotal for achieving practical factorization.