Mitigation Strategy Design for Optimal Augmented Cognition Systems

The development of robust, accurate, real-time cognitive state gauges, based upon operators' physiological data, is an essential pre-requisite to realizing performance improvements through augmented cognition technology. However, gauges that can identify undesirable cognitive states are only useful if corrective action can be taken when the gauges detect problematic states. Thus, in designing augmented cognition systems, it is equally essential to develop mitigation strategies that help operators avoid and/or move out of cognitive states that can cause degradations in operator performance. This report addresses three aspects of mitigation strategy design that need to be considered when deciding what systems should do in response to changes in operator cognitive state: 1) interaction of mitigation strategies with general human-computer interaction principles; 2) task-domain dependency; and 3) correlation between mitigation strategies and specific combinations of gauge values. The treatment of each issue is grounded in specific examples from the design and implementation of multiple augmented cognition systems.