Authors
Mark Higger and Semanti Basu and Moon Hwan Kim and Ryan Waite and Tiffany Tran and Iris Bahar and Steven Sloman and Tom Williams
Venue
IEEE International Conference on Robot-Human Interactive Communication
Publication Year
2026
Causal reasoning plays a key role in human cognition. As such, we hypothesize that robots provided with causal knowledge of task-relevant objects may provide human interactants with more natural and effective cognitive assistance during troubleshooting tasks.
To assess this hypothesis, we present CITA: a novel causally-informed approach to robot-assisted troubleshooting. Through objective analysis and human-subjects experimentation, we demonstrate that causally-informed robot-assisted troubleshooting is not only objectively more efficient, but moreover is perceived as being of higher quality and more intelligent. Overall, our results suggest that robots designed to provide cognitive assistance to humans in task-oriented human-robot interactions should be provided with causal models of the objects involved in those interactions.
