Into the black box

Laypeople's folk theories about generative artificial intelligence chatbots

Bibliographic Data

ID19227915
AuthorsLi Z (0000-0002-6141-5184, Nanyang Technological University), Zhuoman Li (0009-0009-7149-6449, Nanyang Technological University), Nuri Kim (0000-0003-0004-0996, Korea Advanced Institute of Science and Technology, corresponding author), L Chen (0000-0002-8418-1288, Nanyang Technological University), Chen Lou (0000-0002-5506-5835, Nanyang Technological University)
Year2026
Volume13
Issue2
Publication date2026-05-10
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBig Data & Society (JOURNAL)
Journal identifiersISSN: 2053-9517 • E-ISSN: 2053-9517
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/20539517261447838
OpenAlexW7160830950
LanguageEN
References cited61

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

Ambiguity · Construct (python library) · Focus (optics) · Generative grammar · Interpretability · Meaning (existential) · Perception · Representation (politics) · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI

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