Previous research has sought to understand and mitigate deteriorating performance during multitasking while driving, but there have not been any proposed solutions. Our system is an adaptive reading interface that builds upon implicit interface work to improve driving performance in multitasking situations -- as well as the overall multitasking experience. This thesis demonstrates a proof-of-concept closed-loop solution for multitasking while driving and tests its usability through a preliminary study. Our study involved a functional near-infrared spectroscopy (fNIRS) device, driving simulator, and adaptive reading interface. The fNIRS device monitors brain activity and triggers expansion of the reading interface in response to brain activity evoked by the challenges presented by the driving simulation. While this is preliminary research, future work can build upon our contributions. In doing so, this research will provide insight into how to diminish the effects of task-switching while driving.