农业图书情报学报2026，Vol.38Issue(4)：61-70,10.DOI:10.13998/j.cnki.issn1002-1248.25-0750
生成式人工智能迭代中的个人信息安全治理:基于大模型技术演进视角
Governance of Personal Information Security in the Iteration of Generative AI:From the Perspective of the Technological Evolution of Large Models
摘要
Abstract
[Purpose/Significance]The rapid advancement of generative artificial intelligence(AI)is driving societal digital transformation,yet it simultaneously poses unprecedented systemic risks to personal information security due to the large-scale,automated,and complex nature of its data processing.Previous research has lacked exploration of governance pathways that consider endogenous technological evolution and specific model iterations.This paper takes the technological evolution of mainstream,large-scale generative AI models,both domestically and internationally as a starting point,and systematically reveals the impact of generative AI on personal information protection principles across the stages of data collection,model operation,and content generation.The focus is on analyzing how technological innovations in China's DeepSeek,including open-source traceability,decision transparency,and flexible deployment,lay the groundwork for risk-graded governance.This study not only broadens the theoretical perspective on AI governance and promotes the formation of a"technology-institution"collaborative governance paradigm,but also offers innovative and actionable insights for building an agile and effective personal information protection system in China amidst the rapid adoption of generative AI.[Method/Process]This study employs a comparative analysis and inductive research approach.First,it systematically compares the core technological differences among mainstream generative AI models,both domestic and international,across three dimensions:model ecosystem,model capabilities,and deployment methods.Through this comparison,it analyzes the challenges generative AI poses to personal information protection at various stages,including data collection,model operation,and content generation.Second,the study systematically examines the differentiated impacts brought about by DeepSeek's technological iterations on personal information security governance.Building on this foundation,the research proposes a comprehensive governance strategy centered on the principles of inclusiveness and prudence,guided by risk grading,and covering all operational stages of generative AI.This strategy emphasizes the critical role of DeepSeek's technical characteristics in supporting the implementation of this framework.[Results/Conclusions]The research indicates that constructing a risk-graded governance system based on the sensitivity of personal information is an effective approach to balancing security and innovation in generative AI.This system emphasizes distinguishing between sensitive and general information during data collection,achieving traceability and purpose control during model operation,and implementing differentiated security safeguards during content generation.With its technical advantages,including open-source traceability,decision transparency,and flexible deployment,DeepSeek provides technical validation and practical possibilities for graded governance.This facilitates the protection of sensitive personal information in high-risk scenarios while simultaneously fostering technological iteration and application innovation in medium-to low-risk contexts.Future research should further incorporate multi-dimensional governance elements such as industry self-regulation,social coordination,and international collaboration.Empirical analysis should also be conducted to test the applicability and effectiveness of the governance framework,thereby gradually developing a well-rounded personal information security governance scheme that adapts to the dynamic evolution of technology.关键词
生成式人工智能/个人信息安全/DeepSeek/风险分级Key words
generative artificial intelligence/personal information security/deepseek/risk classification分类
社会科学引用本文复制引用
安琳..生成式人工智能迭代中的个人信息安全治理:基于大模型技术演进视角[J].农业图书情报学报,2026,38(4):61-70,10.基金项目
陕西省文化和旅游厅2025年度文化和旅游课题"陕西城乡新型公共文化空间建设研究"(2025WL37) （2025WL37）
