Understanding Risk and Dependency in AI Chatbot Use from User Discourse
This provides early empirical evidence from real-world user discourse on AI safety perceptions and emotional experiences, offering a foundation for future research and governance.
The researchers tackled the limited empirical understanding of psychological risk in AI chatbot use by conducting a large-scale computational thematic analysis of Reddit posts from communities focused on AI-related harm and distress, identifying five experiential dimensions of risk with self-regulation difficulties as most prevalent and fear concentrated in autonomy, control, and technical concerns.
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.