Using PPT to analyze suboptimal human-automation performance

Diagnostic automation aids are designed to improve human performance by increasing accuracy in event detection tasks. However, human-automation performance has frequently fallen short of expectations, particularly when the aid is highly reliable. In those cases, human-automation performance is often suboptimal, in that a human being augmented with a diagnostic aid does more poorly than the automation itself. Previously, there have been only ambiguous explanations for why this occurs, with few suggestions on how to effectively eliminate suboptimal performance. Fortunately, with the advent of a new general theory of task performance, termed Potential Performance Theory (PPT) by D. Trafimow and S. Rice (2008; 2009), one can now determine exactly why suboptimal performance occurs. Results from the present study reveal that inconsistency is the culprit, rather than just poor strategy selection. Furthermore, PPT allows one to determine exactly how much of the performance decrement is because of inconsistency.