Traditional institutional governance assumes that the entity authorized to act is also the entity meaningfully performing judgment. AI-mediated execution architectures increasingly dissolve this coupling, distributing cognition across retrieval systems, orchestration layers, reasoning agents, semantic abstractions, and machine-generated summaries. This paper introduces Execution Attribution Collapse as an emerging governance failure mode in which procedural legitimacy remains visible while substantive cognitive ownership fragments beneath operational execution. The paper argues that future governance architectures must evolve from retrospective oversight toward continuously maintained execution legitimacy attached to operational reality at the moment consequence binds.
• Where does meaningful judgment originate in distributed AI systems? • Can authoritative judgment still be reliably located? • How does distributed cognition weaken traditional accountability assumptions? • Why is explainability insufficient for institutional legitimacy? • What is Execution Attribution Collapse? • What governance capabilities are required to preserve cognitive ownership at T=0?
Investigate how AI-mediated execution architectures fragment meaningful judgment across retrieval systems, orchestration layers, reasoning agents, memory architectures, semantic abstractions, and partial human review, creating conditions where institutions can no longer reliably determine where authoritative judgment originated.
• The Collapse of Traditional Institutional Authority Assumptions Under Distributed AI-Mediated Cognition • From Data Governance to Execution Admissibility • The Desynchronization of Authority
Distributed Cognition, AI-Mediated Judgment, and the Emerging Legitimacy Crisis
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