The Influence of Interdependence on Trust Calibration in Human-Machine Teams

bookPart
In human-machine teams, the strengths and weaknesses of both team members result in dependencies, opportunities, and requirements to collaborate. Managing these interdependence relationships is crucial for teamwork, as it is argued that they facilitate accurate trust calibration. Unfortunately, empirical research on the influence of interdependence on trust calibration during human-machine teamwork is lacking. Therefore, we conducted an experiment (n=80) to study the effect of interdependence relationships (complete independence, complementary independence, optional interdependence, required interdependence) on human-machine trust calibration. Participants collaborated with a virtual agent during a simulated search and rescue task in teams characterized by one of the four interdependencies. A machine-induced trust violation was included in the task to facilitate dynamic trust calibration. Results show that the interdependence relationships during human-machine teamwork influence perceived trust calibration over time. Only in the teams with joint actions (optional and required interdependence) does perceived trust in the machine not recover to its initial pre-violated value. However, results show that the correlation between perceived trust in the machine and machine trustworthiness is strongest in these teams with joint actions, suggesting a more accurate trust calibration process. Overall, our findings provide some first evidence that interdependence relationships during human-machine teamwork influence human-machine trust calibration. © 2024 The Authors.
TNO Identifier
997665
ISBN
978-164368522-9
Source title
3rd International Conference on Hybrid Human-Artificial Intelligence, HHAI Hybrid Human AI Systems for the Social Good, Malmo 10-12 June 2024
Editor(s)
Lorig, F.
Tucker, J.
Lindstrom, A.D.
Dignum, F.
Murukannaiah, P.
Theodorou, A.
Yolum, P.
Pages
300-314