A Capacity Coefficient Method for Characterizing the Impacts of Automation Transparency on Workload Efficiency

Automation can be unreliable. This makes appropriate trust and reliance difficult to calibrate. One solution to building appropriate trust is to increase automation transparency by displaying information to the operator about the technology’s underlying analytical principles. However, displaying this additional information may increase operator workload. The research and development community must balance the competing demands of providing adequate transparency and keeping operator workload low. To investigate the complex effects of transparency on workload, a modeling approach can be used by computing a measure of processing efficiency called the capacity coefficient. We conducted a study to examine the impact of increasing transparency on operator workload using the capacity coefficient. We present the data from one participant with the goal of demonstrating the utility of the capacity coefficient. We discuss how this participant’s data highlights the inferences possible from capacity analysis for measuring the impact of display design and increased transparency on operator workload.