Where does your organization stand?

Four questions, one per principle of the Human in Control framework. Answer honestly about how things work today — not how you would like them to work — and you will get a maturity level and a place to start.

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Principle 01 · Responsibility Cannot Be AutomatedWhen an AI-influenced decision goes wrong, who is accountable?

It is unclear — accountability is sorted out after the fact, if at all.Accountability is defined on paper, but not consistently understood.A named person owns the outcome of each AI-influenced decision.Accountability is clear, reviewed regularly, and adjusts as systems change.

Principle 02 · Autonomy Requires Proportional ControlHow do your control mechanisms scale with what a system can do on its own?

Controls do not reflect how much autonomy a system has.High-stakes decisions are identified, but controls are applied inconsistently.Control levels scale with consequence; critical actions require human sign-off.We continuously reassess control as capabilities and risks evolve.

Principle 03 · Explainability Is a Prerequisite for TrustCan the accountable person explain why a system did what it did?

No — our critical systems are effectively black boxes.Sometimes — it depends on the system and the person.Yes — the accountable person can understand and challenge the logic.Yes, and explainability is tested and maintained as systems change.

Principle 04 · Control Must Be Designed, Not AssumedWhere can a human actually intervene?

Override is not designed in; we assume we could stop it if needed.Some control points exist, but they were bolted on after the fact.Override mechanisms are built in and work in practice.Control points are designed up front and evolve with the system.

Answer all four questions to see your maturity level.

Human in Control

Decision quality under uncertainty.
AI governance with real control.

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