Does Comparing with Generative Artificial Intelligence Harm Self-Esteem? Testing a Model Linking Social Comparison Orientation to Rejection-Identification Process

While the effects of interpersonal social comparison have been widely explored, the potential consequences of human-machine comparison remain understudied. The present survey research investigates how individuals compare themselves to generative artificial intelligence (GAI), by extending the concept of social comparison orientation to human-GAI interactions. Using a large Chinese sample (<i>N</i> = 1302), we examine the relationships between two subtypes of human-GAI comparison orientation (ability-based and opinion-based), self-esteem, perceived identity threat, anthropocentric beliefs, and personal relative deprivation within the framework of the Rejection-Identification Model. The findings reveal that both ability-based and opinion-based comparisons with GAI positively relate to self-esteem, diverging from relevant findings on interpersonal comparisons. In addition, ability-based comparisons with GAI significantly heighten the perceived identity threat, whereas opinion-based comparisons with GAI may alleviate it. Furthermore, anthropocentric beliefs (i.e., human-first attitudes) suppress the negative effect of identity threat on self-esteem, which is also mediated by personal relative deprivation. In addition, a <i>post hoc</i> exploratory multigroup analysis was conducted based on usage frequency. The present study highlights the importance of investigating human-AI comparison and expands the explanatory power of classical concepts and frameworks from the self and identity domains, contributing to psychological interventions aimed at mitigating the potential adverse effects driven by human-machine relationships.