Human Performance Consequences of Automated Decision Aids in States of Sleep Loss

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Objective: The authors investigated how human performance consequences of automated decision aids are affected by the degree of automation and the operator’s functional state. Background: As research has shown, decision aids may not only improve performance but also lead to new sorts of risks. Whereas knowledge exists about the impact of system characteristics (e.g., reliability) on human performance, little is known about how these performance consequences are moderated by the functional state of operators. Method: Participants performed a simulated supervisory process control task with one of two decision aids providing support for fault identification and management. One session took place during the day, and another one took place during the night after a prolonged waking phase of more than 20 hr. Results: Results showed that decision aids can support humans effectively in maintaining high levels of performance, even in states of sleep loss, with more highly automated aids being more effective than less automated ones. Furthermore, participants suffering from sleep loss were found to be more careful in interaction with the aids, that is, less prone to effects of complacency and automation bias. However, cost effects arose that included a decline in secondary-task performance and an increased risk of return-to-manual performance decrements. Conclusion: Automation support can help protect performance after a period of extended wakefulness. In addition, operators suffering from sleep loss seem to compensate for their impaired functional state by reallocating resources and showing a more attentive behavior toward possible automation failures. Application: Results of this research can inform the design of automation, especially decision aids