AI Chatbots

PMR — pp. 1-31 2026-04-02 Original Smiley bots, satisfied citizens? The impact of AI humanization on citizen experience in public services Jinjin Wu, Yifan Chen Abstract This study examines how AI humanization influences citizen experience in public service delivery by integrating the Stereotype Content Model (SCM) and Emotion as Social Information (EASI) theory. Focusing on AI chatbots as a research context, we explore how humanized responses shape perceived warmth and competence and whether effects differ between programmed and non-programmed services through a survey experiment with four vignette-based scenarios. Findings underscore the importance of context-sensitive and carefully calibrated AI design and functioning choices. By linking SCM’s content dimensions with EASI’s affective and inferential mechanisms, the study provides a social-psychological lens to understand citizen–government interactions in AI-driven public administration and provides practical guidance for designing AI-enabled services that remain citizen-friendly while safeguarding core public values.