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| Format: | Recurso digital |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.18284429 |
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Table of Contents:
- <p>The Anthropocentric Fallacy in Agentic AI Governance</p> <p>Why Human-in-the-Loop Control Fails at Machine Speed</p> <p>Abstract</p> <p> </p> <p>As artificial intelligence systems transition from assistive generation to autonomous, agentic execution, governance architectures inherited from human-centric workflows increasingly impose structural limitations. This paper examines the limitations of Human-in-the-Loop (HITL) governance in high-velocity agentic systems, arguing that biological decision latency and cognitive variance introduce measurable performance degradation and systemic inconsistency.</p> <p>Drawing on findings from cognitive science, systems theory, and ensemble machine learning, we demonstrate that synchronous human oversight is poorly matched to millisecond-scale execution environments. We introduce a machine-speed governance framework, referred to as the Digital Senate, which replaces transactional human gating with adversarial multi-agent consensus operating under deterministic policy constraints. Human oversight is repositioned to an asynchronous audit role—Human-on-the-Rail (HOTR)—preserving accountability without constraining execution velocity.</p> <p>This architecture reframes AI governance as a systems engineering problem rather than a supervisory one, offering improved scalability, consistency, and auditability in autonomous decision pipelines. </p> <p> </p>