We describe a novel, model-based approach to augmented cognition. We first discuss a subset of cognitive limitations that are likely to impair performance. We then note traditional approaches to the enhancement of cognitive abilities and their shortcomings, and compare the augmented approach to that of the traditional human-computer interface design. We discuss an example of our approach involving augmenting human ability to allocate attention in tasks such as search and monitoring. The model of attentional processes is then used to develop a framework for an optimal attention allocation process. Finally, we describe a pilot experiment in which observers' eye gaze is monitored and used to help them allocate attention.
['Misha Pavel', 'Guoping Wang', 'Kehai Li']
Augmented cognition: allocation of attention