从用户真实讨论中解析出五类AI聊天机器人心理风险，揭示自控困难与失控恐惧的核心问题。
Understanding Risk and Dependency in AI Chatbot Use from User Discourse
- 基于双社区帖子的多智能体主题分析，提炼出14个主题并归为5大体验维度。
- 发现自控困难是最普遍的心理风险，恐惧主要集中在自主性、控制权和技术风险上。
- 通过BERT情感分类可视化情绪分布，为真实场景下的AI安全研究提供实证基础。
生成式AI正深度融入日常生活，但关于其使用引发的心理风险如何产生、被体验及由用户自我调节的实证理解仍有限。本研究对2023至2025年间来自两个Reddit社区r/AIDangers和r/ChatbotAddiction的帖子进行大规模计算主题分析，聚焦于与AI相关的伤害与痛苦。采用基于Braun与Clarke反思框架的多智能体、大模型辅助主题分析方法，识别出14个重复出现的主题类别，并整合为五个更高阶的体验维度。为进一步刻画情绪模式，使用基于BERT的情感分类器进行情感标注，并可视化各维度的情绪轮廓。研究揭示了五种基于真实用户话语的AI相关心理风险体验维度，其中自控困难最为普遍，恐惧集中于自主性、控制权及技术风险方面。这些结果首次提供了来自真实世界用户经验的实证证据，说明了在非实验室或推测性情境下，人们对AI安全的感知与情绪体验，为未来的AI安全研究、评估与负责任治理奠定了基础。
原文摘要 · Abstract (English)
Generative AI systems are increasingly embedded in everyday life, yet empirical understanding of how psychological risk associated with AI use emerges, is experienced, and is regulated by users remains limited. We present a large-scale computational thematic analysis of posts collected between 2023 and 2025 from two Reddit communities, r/AIDangers and r/ChatbotAddiction, explicitly focused on AI-related harm and distress. Using a multi-agent, LLM-assisted thematic analysis grounded in Braun and Clarke's reflexive framework, we identify 14 recurring thematic categories and synthesize them into five higher-order experiential dimensions. To further characterize affective patterns, we apply emotion labeling using a BERT-based classifier and visualize emotional profiles across dimensions. Our findings reveal five empirically derived experiential dimensions of AI-related psychological risk grounded in real-world user discourse, with self-regulation difficulties emerging as the most prevalent and fear concentrated in concerns related to autonomy, control, and technical risk. These results provide early empirical evidence from lived user experience of how AI safety is perceived and emotionally experienced outside laboratory or speculative contexts, offering a foundation for future AI safety research, evaluation, and responsible governance.
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