Christopher A. Miller

Smart Information Flow Technologies (United States)

Papers

Total Citations

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About

Christopher A. Miller is a leading researcher in human-autonomy teaming, with a focus on designing intelligent systems that can operate effectively under human supervision in uncertain environments. His work bridges the gap between artificial intelligence and human factors, exploring how autonomous systems can communicate their own confidence and limitations to human operators. Miller’s most cited paper, "Towards Self-Confidence in Autonomous Systems" (2016, 9 citations), introduces a framework for enabling machines to assess and express their own certainty—a critical capability for safe and effective human-on-the-loop control in domains like military operations and civilian infrastructure. This contribution addresses a fundamental challenge in modern autonomy: ensuring that human supervisors can trust and calibrate their responses to machine decisions. Miller’s research has influenced the design of adaptive automation, where systems adjust their behavior based on real-time assessments of their own performance. His work is essential reading for students and researchers interested in explainable AI, human-robot interaction, and the future of supervisory control in high-stakes environments.