AI人机交互用户个性化推荐中隐私信息披露影响因素研究

Research on the Influencing Factors of Privacy Information Disclosure in Personalized Recommendations of AI Human-Computer Interaction Users

[目的/意义]以ChatGPT为代表的生成式人工智能的发展为人机交互带来颠覆性影响,也为数据安全与个人信息保护带来更大的冲击与挑战。对AI人机交互用户个性化推荐中隐私信息披露及个人信息保护问题的研究将具有重要的实践价值与意义。[方法/过程]文章通过对15名AI人机交互平台用户进行深度访谈,运用扎根理论研究方法进行编码分析,识别AI人机交互用户个性化推荐中隐私信息披露所涉及的个人信息类型和敏感信息类型,并对用户的隐私意识和影响用户隐私信息披露意愿的客观因素进行分析,进而提出加强隐私信息披露风险规制及个人信息安全保障的对策建议。[结果/结论]基于编码结果,将AI人机交互用户个性化推荐中隐私信息披露的影响因素归纳为用户因素、平台因素、社会环境因素、隐私权衡因素4个维度,以此建构理论分析模型,并作为强化AI人机交互用户个性化推荐中隐私信息披露风险规制及个人信息保护的重要指引。

[Purpose/significance]The development of generative AI represented by ChatGPT has brought disruptive impact on human-computer interaction,as well as greater impact and challenges to data security and personal information protection.Therefore,the research on privacy information disclosure and personal information protection issues in the personalized recommendation of AI human-computer interaction users will have important practical value and significance.[Method/process]Through in-depth interviews with 15 AI human-computer interaction platform users and coding analysis with grounded theory method,the article identifies the types of personal information and sensitive information involved in privacy information disclosure in personalized recommendation of AI human-computer interaction users,and then analyzes users’privacy awareness and objective factors affecting their willingness to disclose privacy information.Finally,the article puts forward the countermeasures and suggestions to strengthen the regulation of privacy information disclosure risks and personal information security protection.[Result/conclusion]Based on the coding results,the influencing factors of privacy information disclosure in AI human-computer interaction user personalized recommendation are summarized into four dimensions:user factors,network platform factors,social environment factors and privacy calculus factors,so as to construct a theoretical analysis model and serve as an important guide to strengthen the regulation of privacy information disclosure risks and personal information protection in AI human-computer interaction user personalized recommendation.