Actionable insight: Building robust human-machine teams through contextual understanding
Context Beats Complexity: Behavior-in-context is more robust and practical than chasing fragile physiological signals.
Proven in Practice: Our PoC shows that by observing the effects of cognitive states on actions, we can predict goals without invasive sensors.
Scalable Impact: This context-first approach accelerates the deployment of effective, ethical, and viable human-machine teams.