GAI hallucinations and user dependence: cognitive-affective responses and individual differences

Generative artificial intelligence (GAI) hallucinations raise questions about how users respond to unreliable outputs from a technology on which they depend. Drawing on the cognitive-affective components of the Interaction of Person-Affect-Cognition-Execution (I-PACE) framework, this study examines the roles of GAI trust, cognitive dissonance, perceived controllability, and frustration in the relationship between perceived hallucinations and GAI dependence, with GAI literacy and self-efficacy as individual-difference moderators. A between-subjects experiment involved 546 participants who viewed the same GAI dialogue labelled as either containing fabricated information or verified as accurate. Participants in the former condition reported lower trust and perceived controllability, greater cognitive dissonance and frustration, and lower dependence scores. In the parallel model, the indirect associations through trust, controllability, and frustration were negative, whereas the indirect association through cognitive dissonance was positive. Higher GAI literacy weakened the positive controllability-dependence association. The remaining moderation hypotheses were not supported under the directional and multiplicity-adjusted criteria. The findings connect users' evaluations of unreliable GAI responses with the difficulties they report in regulating their use. They underscore the importance of examining dependence alongside reliability judgements, cognitive conflict, and emotional reactions when assessing the human consequences of GAI hallucinations.