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February 2, 2026Open Access

From Optional Safety to Architectural Responsibility: AI Governance after Models

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Authors

PKPeter Kahl

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Overview

This article redefines AI governance as a structural necessity for maintaining accountability in advanced systems, highlighting the shift in safety perspectives.

Key Points

  • The central aim is to explore the inadequacies of current AI governance frameworks for physically embedded and agentic systems.
  • Analyzed shifts in AI deployment in defense and industry
  • Critically assessed existing governance structures
  • Reviewed theories of distributed cognition and fiduciary models
  • Identified structural limits in traditional AI governance
  • Reframed delay as a systemic risk
  • Outlined essential governance conditions for accountability under rapid deployment

Cite This Study

Peter Kahl (2026) studied this question.

synapsesocial.com/papers/6980fed9c1c9540dea8115aehttps://doi.org/10.5281/zenodo.18431308
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Also Consider

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  3. 3Why AI Can't Be Governed Like a Steam Engine2026
  4. 4Structural Governance of Autonomous Systems2026
  5. 5A SYSTEMS ARCHITECTURE FOR AI GOVERNANCE Toward an Architecture of Governance in AI Systems2026