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June 11, 20260 citationsOpen Access

The Two-Layer Error in AI Governance: Why Orientation, Not Output, Is the Real Substrate

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NTNarnaiezzsshaa TruongAmerican Rock Mechanics Association

Key Points

  • This paper explores the governance challenges in AI by emphasizing the importance of the orientation layer over mere output control.
  • Examines distinctions between output-layer and orientation-layer governance.
  • Analyzes upstream constraints and continuity in AI interpretive frames.
  • Discusses the implications of orientation drift in AI governance.
  • Identifies that orientation is a critical substrate for AI governance.
  • Argues that governance should focus on architecture rather than just policy.
  • Establishes the importance of understanding the Observe/Orient boundary in regulation.

Abstract

AI governance has concentrated on the output boundary — the deterministic gate that releases or rejects what a model produces. This paper argues that boundary is the symptom, not the substrate. The real governance problem is upstream, at the orientation layer, where a model forms its interpretive frame, maintains continuity, and can drift before any output exists. Through five distinctions — output- versus orientation-layer governance, closure as an upstream constraint, continuity versus determinism, the limits of Gödel analogies, and orientation drift as the substrate problem — it locates governance at the Observe/Orient boundary, the layer at which governance becomes architecture rather than policy.

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Cite This Study

Narnaiezzsshaa Truong (2026) studied this question.

synapsesocial.com/papers/6a2a52d980c8f91e7f39eaf4https://doi.org/10.5281/zenodo.20616807
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Orientation Governance for AI-Enabled Intelligence Production: Why Output-Layer Tradecraft Standards Are Necessary but Insufficient—and What Substrate Governance Adds2026
  2. 2Orientation Profiles, Argument Maps, and Aporia Checkpoints: A Three-Layer Architecture for Substrate Governance of AI-Assisted Intelligence Analysis2026
  3. 3Everyone Is Building "The Solution" to the AI Governance Gap — And Missing the Actual Gap2026
  4. 4Everyone Is Building "The Solution" to the AI Governance Gap — And Missing the Actual Gap2026
  5. 5Substrate Governance: Why Runtime Controls Are Insufficient and What Must Replace Them: A Vendor-Agnostic Framework for Governing AI Agents at the Infrastructure Layer2026