Governance Requirements expressed in Natural Language inherently leave some room for Interpretation. Such flexibility may be necessary in human Governance, but if multiple AI Systems independently interpret the same Requirement, they may produce different Governance Outcomes.

For example, consider the same Requirement stating that a Provider must ensure “appropriate human oversight” for Decisions that may have a significant impact on individuals. The Natural-Language Requirement alone does not uniquely determine what “appropriate human oversight” specifically requires.

Model A might interpret the Requirement as requiring Human Approval before Execution. Model B might determine that Human Review after the Decision is sufficient where the Decision can subsequently be corrected. Model C might interpret Human Intervention as necessary only when a predefined Risk Threshold is exceeded.

Although all three interpretations refer to the same Requirement, they produce substantially different Execution Conditions. If the meaning of Governance is left to the Inference of individual AI Systems, the effective Governance may vary depending on which Model or System is used.

I2EA separates this problem through Structural Translation of Governance Requirements. The Authority to determine what constitutes “appropriate human oversight” belongs to the entity with legitimate Interpretation Authority over the relevant Governance Requirement. Translation Authority does not independently determine a new interpretation. Instead, it transforms the Authorized Interpretation into a Machine-readable Governance Structure, including Scope, Trigger, Required Control, Timing, Execution Condition, Exception, Authority, and Policy Version.

For example, an Authorized Interpretation may establish that where a Decision affects an individual and Significant Impact = TRUE, Human Review is required before Execution, and Execution must not proceed until Approval has been confirmed. Once this Structure is established, the role of the AI System is not to independently reinterpret the meaning of Policy, but to apply the Translated Policy to the Relevant Context.

The Execution Boundary likewise does not interpret the meaning of Policy. It verifies the Decision and Execution Conditions formed through the upstream Governance Process and permits Execution to proceed only where valid Authorization and required Conditions are confirmed.

The purpose of Structural Translation is therefore not to eliminate all Ambiguity from Natural Language. It is to make the Governance-relevant Interpretation explicit under legitimate Authority and transform it into Machine-readable Structure, thereby separating the meaning of Governance from independent Inference by individual AI Systems.