2024 IEEE 6th International Conference on Cognitive Machine Intelligence (CogMI)
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Abstract

The need to enhance the understanding of trust dynamics in human-autonomy teams with intensive longitudinal data is pressing. As the feasibility of autonomous teammates grows, it becomes urgent to investigate how people may cultivate, sustain, and restore their trust in them. However, technological limitations have impeded previous research restricting the type of autonomous agent used. The failure to employ agents capable of executing human-like teamwork behaviors and experimental tasks designed for these teams will impede efforts to understand trust development and calibration. The current study aimed to overcome the constraints of past research by pairing participants with a fully autonomous agent in a virtual testbed. Understanding how trust fluctuates in this testbed could pave the way for a deeper understanding of trust dynamics in human-autonomy teams and lead to more effective collaboration.
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