Data Security Risks and Countermeasures of Generative Artificial Intelligence
[Purpose/significance]The widespread use of generative artificial intelligence has given rise to multiple da-ta security risks.Traditional reactive and centralized governance models seem inadequate to address these new chal-lenges.In contrast,agile governance,with its flexible approach,demonstrates a unique superiority.[Method/process]Firstly,a meticulous examination of the multifaceted risks in data security posed by generative artificial intelligence is conducted.Subsequently,a comparative analysis of the efficacy of three governance models in risk management is car-ried out.It is suggested that China should promptly transition its governance model.Guided by this,a specific gover-nance framework is constructed.[Result/conclusion]The agile governance approach,characterized by its adaptability,flexibility,and inclusiveness,offers a highly effective strategy for addressing data security risks associated with emerg-ing technologies like generative artificial intelligence.It allows for the continuous optimization of the governance sys-tem for generative artificial intelligence data security.Within the agile governance framework,it is essential to embrace the adaptive governance concept of"equal emphasis on prevention and response",construct a resilient governance mechanism that promotes"diverse participation and collaborative interactions",and employ inclusive governance ap-proaches that combine technology with legal measures.This way,a comprehensive framework for ensuring the security of generative artificial intelligence data is constructed.
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