IntroductionGenerative artificial intelligence (GAI) is increasingly integrated into daily decision-making and task performance, as users rely on it to improve productivity, support decision-making, and reduce perceived human error. However, GAI outputs may contain inaccuracies, misleading content, or algorithmic biases. These issues may contribute to uncritical acceptance or excessive dependence among users, potentially posing risks to individuals and third parties. From an individual perspecti
Personality profiles and usage experience are associated with trust and dependence on generative AI: a latent profile analysis
Yunfei Wang
