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