TL;DR
Expand AI autonomy only as control evidence demonstrates that the system and its owners can carry it.
What the paper develops
Autonomy is often discussed as a model capability when it is really a decision about permitted action and recoverable consequence. This paper defines progressive levels of autonomy and the evidence required to move between them. It keeps expansion tied to boundary adherence, exception detection, human intervention, and demonstrated recovery rather than to the impressiveness of a single run.
The operating move
Increase autonomy in stages. Each expansion should be earned by evidence that the system stays within its boundaries, exceptions are caught, recovery works, and an accountable owner can intervene.
WORKFLOWCONTROL EVIDENCEHUMAN OWNER
Inside the white paper
- Progressive autonomy levels tied to real workflow authority
- Control evidence for boundaries, exceptions, intervention, and recovery
- Rollback, stop conditions, and accountable ownership at each level