Adaptive Interface for Management of Bias and Workload Reduction (AMBR)

Advances in aircraft performance and weapons capability have led to a dramatic increase in the tempo of tactical situations facing the combat aviator or UAV controller, reducing the operator's available information processing and decision-making time and resources. Furthermore, the technological and information advances of Network Centric Warfare (NCW) have resulted in an explosion in the complexity and sheer quantity of information that is available to the operator. To counter this increasingly complex operational environment, the Navy requires advanced human/system interface concepts that will make optimal use of the operator's cognitive resources and minimize potential for operator error. The adaptive interface should enhance the flow of information and control between the operator and the vehicle to improve the operator's situation awareness (SA) and decision-making performance while alleviating workload and reducing the effects of cognitive biases, and thus improving survivability, lethality, and ultimately, mission effectiveness. To address this need, we propose to develop a prototype Adaptive Interface for Management of Bias and Workload Reduction (AMBR) that uses computational SA models, operator mental and physical state tracking, and cognitive bias tracking to drive the content, format, and modality of military displays for operation of advanced aviation systems.