The Accountability Vacuum
Thesis
Institutional AI governance fails not from missing policy, but from the absence of a named answer when the system is wrong.
Analysis
Most institutions now possess an AI policy. Few possess the thing the policy was meant to produce: a named individual who answers when the system fails.
The gap between policy and accountability is where exposure accumulates. A policy states that someone should be responsible. Accountability architecture defines who that person is, what they are notified of, and what authority they hold to intervene. When the architecture is absent, the institution has a document — not a defense.
Framework
Accountability Architecture NAME → Who answers when the system fails NOTIFY → What they are told, and how quickly AUTHORITY → What power they hold to intervene REVIEW → When the assignment is re-examined If any element is blank, governance exists on paper only.
Board-Level Questions
For each AI system we operate, who is the named individual accountable for its outcomes?
When the system fails, what are they notified of, and within what timeframe?
What authority does that individual hold to stop or modify the system?
When was the accountability assignment last reviewed — and does the named person still hold the role?
Operating Implication
For every AI system in operation, name the individual accountable for its outcomes. Define what they are notified of, when they are expected to act, and what authority they hold to stop the system. A policy without a named owner is not governance — it is aspiration.
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