Original
Smiley bots, satisfied citizens? The impact of AI humanization on citizen experience in public services
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.
中文
微笑机器人，满意的公民？人工智能拟人化对公共服务中公民体验的影响
摘要
本研究通过整合刻板印象内容模型（SCM）与情绪作为社会信息理论（EASI），考察人工智能拟人化如何影响公共服务供给中的公民体验。研究以AI聊天机器人为情境，借助包含四个情境实验场景的调查实验，探讨拟人化回应如何塑造感知热情与感知能力，以及这些效应在程序化服务与非程序化服务之间是否存在差异。研究发现凸显了情境敏感且审慎校准的AI设计与运行选择的重要性。通过将SCM的内容维度与EASI的情感及推断机制相联结，本研究提供了一个社会心理学视角，以理解AI驱动公共行政中的公民—政府互动，并为设计既能保持公民友好、又能维护核心公共价值的AI赋能服务提供了实践指导。
关键词
人工智能拟人化、公共服务、公民体验、AI聊天机器人、刻板印象内容模型、情绪作为社会信息理论、调查实验、公共行政