AI authority gates: who may propose, decide and execute?
Design authority gates that separate proposal, permission, execution and logging in an AI system.
A component’s capability does not automatically grant authority to act on a real system.
An agentic chain where one model plans, approves and executes makes failures difficult to stop and attribute.
Every sensitive action requires a grant bound to a subject, action, scope, duration and evidence.
What the architecture must make explicit
Capability does not grant authority. Critical systems must separate what proposes, verifies, permits and executes.
Move from a keyword to an inspectable engineering decision
Separate
Decouple probabilistic proposal, validation, permission and physical execution.
Bound
Limit tools, data, actions, duration and environments available to each component.
Refuse
Make missing evidence, timeouts and ambiguity explicit states.
Audit
Retain the applied rule, its inputs, version and resulting decision.
A claim is only as strong as its binding
The gate must evaluate the exact output produced by the exact realization. Integrity, scientific validity and authority are related, but never interchangeable.
Questions that change the design
What does ai authority gates: who may propose, decide and execute? require?
A component’s capability does not automatically grant authority to act on a real system. Capability does not grant authority. Critical systems must separate what proposes, verifies, permits and executes.
Which evidence should be retained?
At minimum: exact realization identity, inputs and outputs, protocol version, measurements, failure cases and the decision rule. Every sensitive action requires a grant bound to a subject, action, scope, duration and evidence.
Does AMF prescribe a particular model?
No. AMF treats the model, runtime, data, tools and deterministic components as candidate materials. Their retention depends on measured contribution and declared constraints.