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About

Anthony R. Selkowitz is a human factors researcher whose work sits at the intersection of human-autonomy teaming, agent transparency, and human-robot interaction. He is best known for his foundational contributions to the Situation Awareness-based Agent Transparency (SAT) model, a framework designed to help human operators maintain accurate understanding of and calibrated trust in autonomous systems operating alongside them. Selkowitz's most influential paper, "Situation awareness-based agent transparency and human-autonomy teaming effectiveness" (2018), has garnered over 327 citations, establishing him as a leading voice in the field. His research consistently examines how the design of user interfaces can communicate an autonomous agent's goals, reasoning, and projected outcomes to human supervisors — a critical challenge as robotic and AI systems take on increasingly complex roles in military and operational environments. Through experimental studies involving autonomous ground robots such as the Autonomous Squad Member and multi-vehicle management systems like IMPACT, Selkowitz demonstrated that transparency information meaningfully shapes operator trust and situational awareness. His body of work provides both theoretical grounding and practical interface design guidance for developers and researchers working to build safer, more effective partnerships between humans and autonomous systems.