Into the black box: Laypeople's folk theories about generative artificial intelligence chatbots
Abstract
This article explores laypeople's folk theories about generative artificial intelligence (GAI) chatbots and the ways in which these theories are constructed. As GAI tools like ChatGPT continue to expand in reach and capabilities, understanding public perceptions of these technologies is increasingly important. Drawing on folk theory as the conceptual framework, we analyze focus group discussions to gather qualitative insights into how users rationalize the mechanisms of GAI chatbots, with particular attention to the challenges of opacity and interpretability in these technologies. Findings reveal three primary areas within users’ folk theories: knowledge sources and mechanisms, perceived characteristics, and user expectations. We find that users construct these theories by interpreting terms like “machine learning,” directly engaging with chatbots to deduce meaning from these experiences, and drawing analogies to familiar objects. Ultimately, these folk theories shape the strategies users develop for interacting with GAI chatbots.
Fields of Study & Subjects
AI in Service Interactions
Ethics and Social Impacts of AI
Artificial Intelligence in Healthcare and Education
Publication details
- Journal / source
- Big Data & Society
- Publisher
- SAGE Publications
- Volume
- 13
- Issue
- 2
- Publication date
- 10 May 2026
- Language
- EN