Abstract
Trust in human-robot collaboration is an essential consideration that relates to operator performance, utilization, and experience. While trust’s importance is understood, the state-of-the-art methods to study trust in automation, like surveys, drastically limit the types of insights that can be made. Improvements in measuring techniques can provide a granular understanding of influencers like robot reliability and their subsequent impact on human behavior and experience. This investigation quantifies the brain-behavior relationships associated with trust manipulation in shared space human-robot collaboration (HRC) to advance the scope of metrics to study trust. Thirty-eight participants, balanced by sex, were recruited to perform an assembly task with a collaborative robot under reliable and unreliable robot conditions. Brain imaging, psychological and behavioral eye-tracking, quantitative and qualitative performance, and subjective experiences were monitored. Results from this investigation identify specific information processing and cognitive strategies that result in identified trust-related behaviors, that were found to be sex-specific. The use of covert measurements of trust can reveal insights that humans cannot consciously report, thus shedding light on processes systematically overlooked by subjective measures. Our findings connect a trust influencer (robot reliability) to upstream cognition and downstream human behavior and are enabled by the utilization of granular metrics.
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