Verbally Soliciting Human Feedback in Continuous Human-Robot Collaboration: Effects of the Framing and Timing of Reminders

Abstract

Humans expect robots to learn from their feedback and adapt to their preferences. However, there are limitations with how humans provide feedback to robots, e.g., humans may give less feedback as interactions progress. Therefore, it would be advantageous if robots could influence humans to provide more feedback during interactions. We conducted a 2x2 between-subjects user study (𝑁 = 71) to investigate whether the framing and timing of a robot’s reminder to provide feedback could influence human interactants. Human-robot interactions took place in the context of Space Invaders, a fast-paced and continuous collaborative environment. Our results suggest that reminders can influence the amount of feedback humans provide to robots, how participants feel about the robot, and how they feel about providing feedback during the interaction.

Publication
Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction (HRI), March 2023
Kate Candon
Kate Candon
PhD Student, Computer Science

My research interests include human-computer interaction, artificial intelligence, machine learning, human-robot interaction, and socially assistive robots.