Impact of Pilot's Expertise on Selection, Use, Trust, and Acceptance of Automation

Automation regroups a variety of advanced tools meant to improve performance and decrease human workload. This article was designed to investigate how different automation solutions, engaging different human-machine cooperation modes, interact with expertise. Aircraft pilots (i.e., experts) and nonpilots (i.e., novices) were presented with a set of simplified flight piloting tasks monitored simultaneously using the Open MATB (Open Multiattribute Task Battery) in four different automation conditions (manual, assisted, cooperative, and supervisory control). Experts' performances at the Open MATB were higher than those of novices. Experts also exhibited a lower level of workload. Apart from function delegation, where no human performance is required, automation solutions benefit experts and novices similarly. Participants were then asked to choose repeatedly between the four automation conditions. Experts and novices exhibited different strategies. Novices spread their choices over the different automation conditions, whereas experts clearly favor cooperative control, the automation solution that enhanced their expertise.

Automated summary

Experts outperformed novices in the Open MATB and exhibited lower workload levels. Automation solutions benefit both experts and novices similarly, with experts clearly favoring cooperative control.