Adaptive Change in the Type of Automation Support Reduces the Cost of Imperfect Decision Aids in a Simulated Battlefield Engagement Task

Abstract

Automation that is meant to aid the human operator may actually be detrimental to performance, particularly if faulty decision recommendations are provided (decision automation), as opposed to prioritized or integrated information advisories that are incorrect (information automation). Because automation can be imperfect, operator over-reliance on decision automation can degrade performance. The present study examined whether temporary adaptive changes in the type and level of automation—-between decision and information automation, or between decision automation and manual performance—–could mitigate the cost of automation imperfection in a combat engagement selection task. Twelve participants were provided with two types of automation (decision and information) and also performed the task manually. In three conditions, the type of automation was alternated during performance of the task over three blocks of trials. In all three conditions, decision automation was provided in the first and third blocks of the task, with the middle block requiring the use of decision automation, information automation, or manual performance. The accuracy of engagement decisions improved in the third block with decision automation when it was preceded by a temporary adaptive change to information automation. No such improvement occurred when decision automation was used throughout the task or when the adaptive change involved a temporary return to manual performance. This suggests that providing the user with short periods of information automation can help mitigate some of the costs of imperfect decision automation by keeping the operator in the decision-making loop.

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