Presentation
62. Quantifying Trust Evolution Through Predictability of Compliance Behavior: A Dynamical Systems Perspective
SessionPoster Session 2
DescriptionRecurrence quantification analysis (RQA) is a nonlinear technique for modeling dynamic patterns in complex systems (Riley & Van Orden, 2005). The application of RQA spans many fields, but notably, has been used to analyze communication patterns and psychological data to understand team behaviors and social dynamics, such as coordination, cooperation, and trust (Mitkidis et al., 2015; Tolston et al., 2018; Grimm et al., 2018; Demir et al., 2021). Despite advancements in the application of RQA for understanding human automation team interactions, the potential of RQA to dynamically characterize trust measures remains largely unexplored (Landfair et al., 2021). These may reveal novel insight into how trust changes in time and across context. In this paper we address this gap in application by investigating compliance decisions over time to quantify the predictability of trust’s nonlinear development in dynamic HAT interactions.
Event Type
Poster
TimeThursday, September 12th5:30pm - 6:30pm MST
LocationMcArthur Ballroom
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