Human Perceptions of a Curious Robot that Performs Off-Task Actions

Researchers have proposed models of curiosity as a means to drive robots to learn and adapt to their environments. While these models balance goal- and exploration-oriented actions in a mathematically principled manor, it is not understood how users perceive a robot that pursues off-task actions. Motivated by a model of curiosity based on intrinsic rewards, we conducted three online video-surveys with a total of 264 participants, evaluating a variety of curious behaviors. Our results indicate that a robot’s off-task actions are perceived as expressions of curiosity, but that these actions lead to a negative impact on perceptions of the robot’s competence. When the robot explains or acknowledges its deviation from the primary task, this can partially mitigate the negative effects of off-task actions. CCS CONCEPTS • Applied computing $\rightarrow$Psychology; • Human-centered computing $\rightarrow$Empirical studies in interaction design. ACM Reference Format: Nick Walker, Kevin Weatherwax, Julian Allchin, Leila Takayama, and Maya Cakmak. 2020. Human Perceptions of a Curious Robot that Performs Off- Task Actions. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’20), March 23–26, 2020, Cambridge, United Kingdom. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3319502.3374821