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

Bibliographic Data

ID22004590
AuthorsYangkun Huang (0000-0002-1521-1981, Tsinghua University), Yuan Gao (0000-0001-8565-1790, Shanghai Jiao Tong University, corresponding author), Xucheng Cao (0000-0001-5814-7222, City University of Hong Kong)
Year2025
Volume28
Issue11
Pages749-755
Publication date2025-11-01
Open AccessYes
TypeARTICLE
VenueCyberpsychology Behavior and Social Networking (JOURNAL)
Journal identifiersISSN: 2152-2715 • E-ISSN: 2152-2723
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/21522715251393008
PMID41234062
OpenAlexW4416232563
LanguageEN
Citations received1
References cited46

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 (N = 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 post hoc 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

Anthropocentrism · Generative grammar · Harm · Interpersonal communication · Social identity theory · Artificial Intelligence in Healthcare and Education · Death Anxiety and Social Exclusion · Psychology of Moral and Emotional Judgment

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