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April 1, 20260 citationsOpen Access

Authorization Is Not Settlement: Why Pre-Execution Governance and Decision Evidence Closure Are Independent Infrastructure Requirements

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YCYuchia Chang

Key Points

  • To clarify the difference between authorization and settlement in AI governance and address structural gaps in current systems.
  • Identified five structural gaps in current AI governance surrounding authorization and settlement.
  • Proposed a framework treating authorization and settlement as separate yet adjacent components.
  • Outlined specific interface requirements for effective governance.
  • Highlighted persistent gaps in cross-step intent reconstruction for authorized actions.
  • Noted deficiencies in provider-side learning from authorized queries.
  • Proposed the need for tamper-proof evidence chains in audit ledgers to ensure accountability.

Abstract

Enterprise AI governance increasingly relies on pre-execution authorization gates. However, authorization and settlement address fundamentally different questions. Authorization determines whether an act may occur. Settlement determines whether responsibility for that act actually closed. This paper identifies five structural gaps that persist even under perfect authorization: Cross-step intent reconstruction from individually authorized actions Provider-side learning from authorized queries Absence of tamper-proof evidence chains in append-only audit ledgers Lack of formal closure conditions for multi-step workflows No special handling for irreversible actions We propose that authorization and settlement be treated as adjacent layers in a governance stack rather than as a single mechanism, and outline the interface requirements between them. P11 in OIA Research Series. v1.0.

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Cite This Study

Yuchia Chang (2026) studied this question.

synapsesocial.com/papers/69ccb71716edfba7beb88ed6https://doi.org/10.5281/zenodo.19338864
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