When Automation Fails - Investigating Cognitive Stability and Flexibility in a Multitasking Scenario

Managing multiple tasks simultaneously often results in performance decrements due to limited cognitive resources. Task prioritization, requiring effective cognitive control, is a strategy to mitigate these effects and is influenced by the stability-flexibility dilemma. While previous studies have investigated the stability-flexibility dilemma in fully manual multitasking environments, this study explores how cognitive control modes interact with automation reliability. Our findings demonstrate that overall task performance benefits from a flexible cognitive control mode when automation is reliable. However, when automation is unreliable, a stable cognitive control mode improves manual takeover performance, though this comes at the expense of secondary task performance. Furthermore, cognitive control modes and automation reliability affect various eye-tracking metrics and mental workload, highlighting the importance of incorporating these factors into the design of adaptive assistance systems, particularly in the perceive stage.