Understanding Teenagers’ Mental Models of Generative AI : Insights from Drawings and Interviews
Haolei Liu, Zhenyi Tang · Proceedings of the Association for Information Science and Technology · 2025
ABSTRACT While Gen AI tools are rapidly reshaping how we learn, work, and create, little is known about how teenagers—digital natives yet non‐professional users—perceive this emerging technology. To address this gap, this study conducted semi‐structured interviews with 20 teenagers in China to investigate their understanding of Gen AI and used thematic analysis to identify common themes in their drawings and responses. We found that: 1) Teenagers' mental models of Gen AI can be divided into four categories: technological, procedural, functional, and comparative; 2) Mental models' characteristics include a high degree of technical trust, and a willingness to anthropomorphize Gen AI. These findings contribute to a better understanding of teens’ cognition about Gen AI, providing implications for AI literacy education of young people and the interactive design of Gen AI platforms and tools.