情报杂志2026，Vol.45Issue(3)：86-95,10.DOI:10.3969/j.issn.1002-1965.2026.03.012
生成式AI交互情境下用户隐私风险自适应模型构建
Construction of User Privacy Risk Adaptive Model in the Generative AI Interaction Context
摘要
Abstract
[Purpose]In the context of generative artificial intelligence(Gen AI)interactions,users'privacy information disclosure behav-iors exhibit highly complex,contextualized,and dynamic characteristics.A deep exploration of the entire process of privacy disclosure in users'sustained interactions with Gen AI can reveal the intricate psychological and behavioral mechanisms underlying privacy decision-making in human-AI interaction,thereby providing critical theoretical support for building trustworthy AI systems.[Method]Drawing on privacy calculus theory,protection motivation theory,and the stimulus-organism-response model as theoretical frameworks,data were collected through semi-structured interviews.Thematic analysis was employed,combining manual coding with GPT-assisted coding,to i-dentify core themes of users'adaptive processes to privacy risks in Gen AI contexts.[Result/Conclusion]A dynamic integrative model of user privacy disclosure in Gen AI interactions is proposed,comprising three core components:one is the triggering factors,including social information,privacy policy,empirical threat,and situational demand;the second is the decision-making process,including privacy inva-sion risks perception,functional benefit perception,and coping appraisal;the third is the behavioral response,including adaptive and non-adaptive coping strategies.The findings advance the understanding of privacy disclosure behaviors in human-AI interactions and offer im-plications for designing more privacy-aware Gen AI systems.关键词
Gen AI/用户隐私风险/隐私披露/隐私计算理论/保护动机理论/刺激—机体—反应模型Key words
Gen AI/user privacy risk/privacy disclosure/privacy calculus theory/protection motivation theory/stimulus-organism-re-sponse model分类
社会科学引用本文复制引用
樊舒,王雪绮,杨婷,董晶..生成式AI交互情境下用户隐私风险自适应模型构建[J].情报杂志,2026,45(3):86-95,10.基金项目
国家社会科学基金青年项目"面向智慧图书馆多模态交互场景的知识服务效能提升研究"(编号:24CTQ001)研究成果. （编号:24CTQ001）
