Multitasking is a universal behaviour that allows multiple tasks to be simultaneously attended to. Although essential, multitasking is mentally demanding which can lead to performance costs (i.e., missed alarms and delayed reaction times), especially in 24/7 jobs. To minimize these costs, automation aids (i.e., automation that controls a task) have been used to reduce workload. However, the impact on multitasking performance due to task-related demands and control switching remains unclear. From a pilot study (N=9) data will be presented on participants who completed one of two Multi-Attribute Task Battery II (MAT-B II) scenarios with an alarm reaction time, resource management, and tracking task with automation aid. The scenarios included a) automation in six 10-minute blocks and b) automation in two 30-minute blocks. Workload measures were collected using wearables including eye-tracking glasses, headband functional near-infrared spectroscopy, an activity watch, and the subjective NASA – Task Load Index. A linear mixed model will be used and presented at the conference to: 1) Compare the effects of the scenarios (i.e., with vs without automation 2) Examine the effects of switching control (the frequency and duration of automation) on multitasking performance 3) Assess the impact of these factors on workload It is anticipated that multitasking performance will differ between the scenarios. In addition, the frequent automation control switches will be associated with greater errors, slower reaction time, and greater tracking and workload variance. These findings could drive technologies with a human-centred focus, such as refining human-machine interfaces to optimise human multitasking performance.