聊天机器人信任源于设计诱导而非真实可靠，用户需警惕认知偏差影响。
Why do we Trust Chatbots? From Normative Principles to Behavioral Drivers
- 将聊天机器人视为受组织目标驱动的销售员，揭示其信任机制本质。
- 用户信任常由交互设计引发的认知偏差塑造，非基于实际可信表现。
- 适合关注AI伦理、人机交互与用户心理的研究者和从业者阅读。
随着聊天机器人日益模糊自动化系统与人类对话的界限，对其信任基础的审视愈发重要。尽管监管框架通常从规范性角度定义信任，但用户对聊天机器人的信任往往源于行为机制。在许多情况下，这种信任并非通过展现可信度获得，而是由交互设计选择利用认知偏差来影响用户行为。基于此，我们提出应将聊天机器人重新定位为受部署机构目标驱动的高超销售人员。我们认为，‘信任’一词下共存的多种概念混淆了心理信任形成与规范性可信性的关键差异。弥合这一差距需要进一步研究及更有力的支持机制，以帮助用户合理校准对对话式人工智能系统的信任。
原文摘要 · Abstract (English)
As chatbots increasingly blur the boundary between automated systems and human conversation, the foundations of trust in these systems warrant closer examination. While regulatory and policy frameworks tend to define trust in normative terms, the trust users place in chatbots often emerges from behavioral mechanisms. In many cases, this trust is not earned through demonstrated trustworthiness but is instead shaped by interactional design choices that leverage cognitive biases to influence user behavior. Based on this observation, we propose reframing chatbots not as companions or assistants, but as highly skilled salespeople whose objectives are determined by the deploying organization. We argue that the coexistence of competing notions of "trust" under a shared term obscures important distinctions between psychological trust formation and normative trustworthiness. Addressing this gap requires further research and stronger support mechanisms to help users appropriately calibrate trust in conversational AI systems.
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