关键词: 大模型, 知识产权突发风险, 风险预警, 处置机制, 协同治理

Abstract: The in-depth application of generative artificial intelligence has endowed intellectual property (IP) risks associated with large models with new notable characteristics, namely sudden onset, high transmissibility and severe destructiveness, which have posed substantial challenges to conventional governance frameworks. This study focuses on the IP emergencies triggered by the misuse of large model technologies, and aims to construct a response and disposal mechanism integrating intelligent early warning, rapid handling and collaborative coordination. First, this study establishes a multidimensional monitoring indicator system, multi-source data perception framework and dynamic grading rules to achieve precise risk identification and tiered classification. Subsequently, this study designs a standardized disposal workflow centered on immediate containment, evidence preservation and blockchain-based forensic storage, which ensures rapid interruption of risk propagation and provides solid support for subsequent legal accountability. Finally, this study develops a multi-stakeholder collaborative linkage mechanism covering government-enterprise cooperation, cross-sectoral coordination and cross-border interaction, so as to integrate resources, resolve jurisdictional conflicts and generate synergistic effects in risk prevention and control. The proposed mechanism aims to realize a paradigm shift from passive remediation to proactive prevention, and provides a theoretical framework and practical pathways for building an agile and efficient governance system for IP risks in the context of large models.

Key words: large models, intellectual property emergency risks, risk early warning, disposal mechanism, collaborative governance