Stephanie M. Merritt

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OBJECTIVE We provide an empirical demonstration of the importance of attending to human user individual differences in examinations of trust and automation use. BACKGROUND Past research has generally supported the notions that machine reliability predicts trust in automation, and trust in turn predicts automation use. However, links between user(More)
OBJECTIVE This study is the first to examine the influence of implicit attitudes toward automation on users' trust in automation. BACKGROUND Past empirical work has examined explicit (conscious) influences on user level of trust in automation but has not yet measured implicit influences. We examine concurrent effects of explicit propensity to trust(More)
OBJECTIVE A self-report measure of the perfect automation schema (PAS) is developed and tested. BACKGROUND Researchers have hypothesized that the extent to which users possess a PAS is associated with greater decreases in trust after users encounter automation errors. However, no measure of the PAS currently exists. We developed a self-report measure(More)
OBJECTIVE We present alternative operationalizations of trust calibration and examine their associations with predictors and outcomes. BACKGROUND It is thought that trust calibration (correspondence between aid reliability and user trust in the aid) is a key to effective human-automation performance. We propose that calibration can be operationalized in(More)
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