Lost in the Story: The Impact of Narrative with a Direction-Giving Robot

Sharing a story alongside an expository response is inherently human, often enhancing communication by adding personal details based on our unique experiences to what we say. When used in a task environment, narratives may be used to exploit measurable effects, such as on memory recall or interaction engagement. With the increasing presence of social robots in everyday environments, it remains unclear whether narrative communication from robots (e.g. “This picture shows a family who recently...”) instead of a factual description yields similar benefits to those observed in human-human interactions. In this paper, we develop and study a direction-giving robot, comparing three styles of navigation instruction: narrative with landmarks, landmarks only, and baseline without landmarks. We evaluate the effects of these conditions on recall, task success, and social acceptability factors (N=38) using a Furhat robot receptionist in a lab environment.
Our findings show that landmark-based navigation significantly enhances perceived usefulness, task success, and social acceptability compared to baseline. Furthermore, narrative-based navigation led to significantly higher recall of individual landmarks and improved perceptions of the robot’s adaptability. These results suggest that narratives can play a practical role in enhancing task-based HRI, particularly in scenarios that demand long-term engagement, user-centered adaptability, or memory retention (e.g. education, or explainability in AI systems).
This work contributes to the broader conversation on incorporating human-like conversational features in robots and highlights narratives as a potential tool for designing more effective human-robot interactions.