Opting Out of Generative AI: a Behavioral Experiment on the Role of Education in Perplexity AI Avoidance
Roberto Ulloa, Juhi Kulshrestha, Celina Kacperski

TL;DR
This study explores how education influences avoidance of conversational AI, revealing that lower education levels correlate with higher avoidance, which may contribute to digital inequalities in AI access.
Contribution
It provides empirical evidence linking education levels to conversational AI avoidance, highlighting the importance of inclusive design for equitable technology access.
Findings
Higher CAI avoidance among lower-educated participants (~74.4%)
Education significantly predicts CAI avoidance after controlling for other factors
Structural models confirm education's central role in AI adoption behaviors
Abstract
The rise of conversational AI (CAI), powered by large language models, is transforming how individuals access and interact with digital information. However, these tools may inadvertently amplify existing digital inequalities. This study investigates whether differences in formal education are associated with CAI avoidance, leveraging behavioral data from an online experiment (N = 1,636). Participants were randomly assigned to a control or an information-seeking task, either a traditional online search or a CAI (Perplexity AI). Task avoidance (operationalized as survey abandonment or providing unrelated responses during task assignment) was significantly higher in the CAI group (51%) compared to the search (30.9%) and control (16.8%) groups, with the highest CAI avoidance among participants with lower education levels (~74.4%). Structural equation modeling based on the theoretical…
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Taxonomy
TopicsAI in Service Interactions · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI
