In Generative AI We (Dis)Trust? Computational Analysis of Trust and Distrust in Reddit Discussions
Year: 2026
Type: article
Abstract: The rise of generative AI (GenAI) has impacted many aspects of life. As these systems become embedded in everyday practices, understanding public trust in them also becomes essential for responsible adoption and governance. Prior work on trust in AI has largely drawn from psychology and human–computer interaction, but there is a lack of computational, large-scale, and longitudinal approaches to measuring trust and distrust in GenAI and large language models. We present the first computational study of Trust and Distrust in GenAI, using a multi-year Reddit dataset (2022–2025) spanning 39 subreddits and 230,576 posts. Crowd-sourced annotations of a representative sample were combined with classification models for scale analysis. Our results show that Trust and Distrust are nearly balanced over time, although Trust modestly outweighs Distrust. Technical performance and usability dominate as dimensions for both categories, while personal experience is the most frequent reason shaping attitudes. Distinct patterns also emerge across trustor groups: while industry professionals and tech leaders predominantly express Trust in GenAI, Distrust remains more prevalent among AI ethicists, journalists, and the general public. Our results provide a methodological framework for large-scale Trust analysis and insights into evolving public perceptions towards GenAI.
DOI: 10.1162/tacl.a.744
Authors: Aria Pessianzadeh, Naima Sultana, Hildegarde Van den Bulck, David Gefen, Shahin Jabbari, Rezvaneh Rezapour
Institution: Drexel University
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
Funder: Drexel University
OpenAlex ID: W4415950396