Exploring dimensions of perceived anthropomorphism in conversational AI: Implications for human identity threat and dehumanization
Yejin Lee, Sang-Hwan Kim · Computers in Human Behavior Artificial Humans · 2025
This study aims to identify humanlike traits in conversational AI (CAI) that influence human identity threat and dehumanization, and to propose design guidelines to mitigate these effects. An online survey was conducted with 323 participants. Factor analysis revealed four key dimensions of perceived anthropomorphism in CAI: Self-likeness, Communication & Memory, Social Adaptability, and Agency. Structural equation modeling showed that Self-likeness heightened both perceived human identity threat and dehumanization, whereas Agency significantly moderated these effects while also directly mitigating dehumanization. Social Adaptability generally reduced perceived human identity threat but amplified it when combined with high Self-likeness. Furthermore, younger individuals were more likely to experience perceived human identity threat and dehumanization, underscoring the importance of considering user age. By elucidating the psychological structure underlying users’ perceptions of CAI anthropomorphism, this study deepens understanding of its psychosocial implications and provides practical guidance for the ethical design of CAI systems.