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Description
The prevalence of autonomous technology is advancing at a rapid rate and is becoming more sophisticated. As this technology becomes more advanced, humans and autonomy may work together as teammates in various settings. A crucial component of teaming is trust, but to date, researchers are limited in assessing trust calibration dynamically in human-autonomy teams. Traditional methods of measuring trust (e.g., Likert scale questionnaires) capture trust after the fact or at a specific time. However, trust fluctuates, and determining what causes this might give machine designers insight into how machines can be improved upon so that operator’s trust towards the machines is more properly calibrated. This thesis aimed to assess the validity of an interaction-based metric of trust: anticipatory pushing of information. Anticipatory pushing of information refers to teammate A anticipating the needs of teammate B and pushing that information to teammate B. It was hypothesized there would be a positive relationship between the frequency of anticipatory pushing and self-reported trust scores. To test this hypothesis, text chat data and self-reported trust scores were analyzed in a previously conducted study in two different sessions (routine and degraded). Findings indicate that the anticipatory pushing of information and the self-reported trust scores between the human-human pairs in the degraded sessions were higher than the routine sessions. In degraded sessions, the anticipatory pushing of information between the human-human pairs was associated with human-human trust.
ContributorsBhatti, Shawaiz (Author) / Cooke, Nancy (Thesis advisor) / Chiou, Erin K (Committee member) / Gutzwiller, Robert (Committee member) / Arizona State University (Publisher)
Created2021