Trust plays a fundamental role in shaping the willingness of users to engage and collaborate with artificial intelligence (AI) systems. Yet, measuring user trust remains challenging due to its complex and dynamic nature. While traditional survey methods provide trust levels for long conversations, they fail to capture its dynamic evolution during ongoing interactions. Here, we present VizTrust, which addresses this challenge by introducing a real-time visual analytics tool that leverages a multi-agent collaboration system to capture and analyze user trust dynamics in human-agent communication. Built on established human-computer trust scales-competence, integrity, benevolence, and predictability-, VizTrust enables stakeholders to observe trust formation as it happens, identify patterns in trust development, and pinpoint specific interaction elements that influence trust. Our tool offers actionable insights into human-agent trust formation and evolution in real time through a dashboard, supporting the design of adaptive conversational agents that responds effectively to user trust signals.

翻译：信任在塑造用户与人工智能系统互动和协作意愿方面起着基础性作用。然而，由于信任具有复杂且动态的特性，测量用户信任仍然具有挑战性。传统的调查方法虽然能为长对话提供信任水平评估，但无法捕捉其在持续交互过程中的动态演变。本文提出VizTrust，通过引入一种实时可视化分析工具来解决这一挑战，该工具利用多智能体协作系统来捕捉和分析人机交互中的用户信任动态。基于已确立的人机信任量表——能力、诚信、善意和可预测性——VizTrust使利益相关者能够实时观察信任形成过程，识别信任发展模式，并精确定位影响信任的具体交互要素。我们的工具通过仪表板实时提供关于人机信任形成与演化的可操作见解，支持设计能够有效响应用户信任信号的自适应对话智能体。