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Abstract
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OBJECTIVE: An experiment used the workload capacity measure C(t) to quantify the processing efficiency of human-automation teams and identify operators' automation usage strategies in a speeded decision task.
BACKGROUND: Although response accuracy rates and related measures are often used to measure the influence of an automated decision aid on human performance, aids can also influence response speed. Mean response times (RTs), however, conflate the influence of the human operator and the automated aid on team performance and may mask changes in the operator's performance strategy under aided conditions. The present study used a measure of parallel processing efficiency, or workload capacity, derived from empirical RT distributions as a novel gauge of human-automation performance and automation dependence in a speeded task.
METHOD: Participants performed a speeded probabilistic decision task with and without the assistance of an automated aid. RT distributions were used to calculate two variants of a workload capacity measure, COR(t) and CAND(t).
RESULTS: Capacity measures gave evidence that a diagnosis from the automated aid speeded human participants' responses, and that participants did not moderate their own decision times in anticipation of diagnoses from the aid.
CONCLUSION AND APPLICATION: Workload capacity provides a sensitive and informative measure of human-automation performance and operators' automation dependence in speeded tasks.
Language: en |