VizTrust: A Visual Analytics Tool for Capturing User Trust Dynamics in Human-AI Communication
This addresses the problem of designing adaptive conversational agents for users by providing real-time insights into trust dynamics, though it is incremental as it builds on existing trust scales.
The researchers tackled the challenge of measuring dynamic user trust in human-AI interactions by developing VizTrust, a real-time visual analytics tool that captures and analyzes trust evolution during ongoing conversations, enabling stakeholders to observe trust formation and identify influencing factors.
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.