A Field Guide to Decision Making
This addresses the problem of improving decision-making for individuals in executive roles, but it appears incremental as it builds on existing ideas of human-AI collaboration without introducing a new paradigm.
The paper tackles the challenge of high-consequence decision-making under uncertainty, limited resources, and time constraints, proposing that machine intelligence can augment human cognition to improve situational awareness and decision coherence.
High-consequence decision making demands peak performance from individuals in positions of responsibility. Such executive authority bears the obligation to act despite uncertainty, limited resources, time constraints, and accountability risks. Tools and strategies to motivate confidence and foster risk tolerance must confront informational noise and can provide qualified accountability. Machine intelligence augments human cognition and perception to improve situational awareness, decision framing, flexibility, and coherence through agentic stewardship of contextual metadata. We examine systemic and behavioral factors crucial to address in scenarios encumbered by complexity, uncertainty, and urgency.