Measuring Individual Differences in the Perfect Automation Schema

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 assessing two proposed PAS factors: high expectations and all-or-none thinking about automation performance. METHOD: In two studies, participants responded to our PAS measure, interacted with imperfect automated aids, and reported trust. RESULTS: Each of the two PAS measure factors demonstrated fit to the hypothesized factor structure and convergent and discriminant validity when compared with propensity to trust machines and trust in a specific aid. However, the high expectations and all-or-none thinking scales showed low intercorrelations and differential relationships with outcomes, suggesting that they might best be considered two separate constructs rather than two subfactors of the PAS. All-or-none thinking had significant associations with decreases in trust following aid errors, whereas high expectations did not. Results therefore suggest that the all-or-none thinking scale may best represent the PAS construct. CONCLUSION: Our PAS measure (specifically, the all-or-none thinking scale) significantly predicted the severe trust decreases thought to be associated with high PAS. Further, it demonstrated acceptable psychometric properties across two samples. APPLICATION: This measure may be used in future work to assess levels of PAS in users of automated systems in either research or applied settings.