Title
Robot Capability and Intention in Trust-Based Decisions Across Tasks
Abstract
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.
Year
DOI
Venue
2019
10.1109/HRI.2019.8673084
2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
Keywords
Field
DocType
Robots,Task analysis,Unmanned aerial vehicles,Estimation,Cognitive science,Automation,Meteorology
Task analysis,Computer science,Delegate,Automation,Human–computer interaction,Delegation,Robot
Conference
ISSN
ISBN
Citations 
ACM/IEEE Conference on Human Robot Interaction (HRI), 2019
978-1-5386-8555-6
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Yaqi Xie111.37
Indu P Bodala200.34
Desmond Ong3105.23
David Hsu482450.86
Harold Soh59017.53