Robot Capability and Intention in Trust-based Decisions across Tasks, Xie Yaqi★, Indu Prasad★, Desmond Ong, David Hsu and Harold Soh ★, ACM/IEEE Conference on Human Robot Interaction (HRI), 2019

In this paper, we present results from a human-subject study designed to explore two facets of human mental models of robots - inferred capability and intention - and their relationship to overall trust and eventual decisions. In particular, we examine delegation situations characterized by uncertainty, and explore how inferred capability and intention are applied across different tasks. We develop an online survey where human participants decide whether to delegate control to a simulated UAV agent. Our study shows that human estimations of robot capability and intent correlate strongly with overall self-reported trust. However, overall trust is not independently sufficient to determine whether a human will decide to trust (delegate) a given task to a robot. Instead, our study reveals that estimations of robot intention, capability, and overall trust are integrated when deciding to delegate. From a broader perspective, these results suggest that calibrating overall trust alone is insufficient; to make correct decisions, humans need (and use) multi-faceted mental models when collaborating with robots across multiple contexts.

## Resources

You can find our paper here. Check out our repository here on github

## Citation

Please consider citing our paper if you build upon our results and ideas.

Xie Yaqi★, Indu Prasad★, Desmond Ong, David Hsu and Harold Soh ★, “Robot Capability and Intention in Trust-based Decisions across Tasks”, ACM/IEEE Conference on Human Robot Interaction (HRI), 2019

@inproceedings{xie2019robot,
title={Robot Capability and Intention in Trust-Based Decisions Across Tasks},
author={Xie, Yaqi and Bodala, Indu P and Ong, Desmond C and Hsu, David and Soh, Harold},
booktitle={2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)},
pages={39--47},
year={2019},
organization={IEEE}}