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When artificial intelligence performs more of the thinking, who still carries the authority—and who answers when the system is wrong?Retained Command: Human Authority, Public Responsibility, and the Law of Delegated Cognition examines one of the central governance problems of the AI age: institutions may delegate analysis, prediction, drafting, recommendation, and even execution to increasingly capable systems, but responsibility cannot simply migrate into the machine.Daniel J. Schendzielos, J.D., Ph.D., develops the doctrine of Retained Command as a practical framework for preserving meaningful human authority when cognition is delegated to technology. Drawing upon law, aviation, medicine, public administration, professional responsibility, human factors, and emerging international AI governance, the book argues that merely keeping a "e;human in the loop"e; is not enough.Real command requires more.It requires identifiable authority, bounded delegation, competence, access to material information, sufficient time to intervene, effective override and fallback procedures, a reconstructable decision record, meaningful reasons, genuine contestability, and the institutional capacity to correct both individual errors and systemic failures.The book examines how responsibility can become diluted through organizational design, vendor relationships, automation bias, nominal oversight, inaccessible decision systems, and increasingly autonomous agents. It also explains why sophisticated automation and human accountability are not opposites. Properly designed institutions can distribute cognitive work broadly while preserving an identifiable office capable of authorizing, questioning, explaining, reconsidering, and repairing consequential decisions.Part legal analysis, part governance framework, and part institutional design doctrine, Retained Command offers a structured approach for organizations confronting the growing power of artificial intelligence.For lawyers, judges, regulators, executives, physicians, pilots, educators, scholars, public officials, and policy makers, this book addresses the question that will increasingly define accountable AI governance:When the system acts, who still answers?
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