01 · Working principle
Ownership is a system property
A workflow is human-owned when authority, evidence, uncertainty, and escalation are visible at every consequential step. A reviewer should be able to tell what the AI contributed, what data supported it, who approved the decision, and what limit or dissent remained.
02 · Working principle
Five visible controls
Treat these controls as requirements, not interface decoration.
- A scoped question and named decision owner.
- Deterministic metrics with definitions and provenance.
- Generated content labeled and separated from source evidence.
- Explicit approval, revision, or rejection by an authorized person.
- An audit trail that connects action and follow-up to the decision.
03 · Working principle
The practical boundary
Hospital operating work includes competing priorities and incomplete evidence. AI can help leaders inspect the record and prepare options, but it should not convert uncertainty into false confidence or cross into patient-level clinical recommendation behavior.
Executive checklist
What leaders should ask next
- Where can a person inspect and challenge the evidence?
- Which outputs are generated rather than calculated?
- Who owns approval and escalation?
- Can a later reviewer reconstruct the decision?
Interpretation boundary
Limits to keep visible
- This framework does not imply autonomous scheduling, bed assignment, or clinical action.
- Operational associations do not establish why an outcome changed.
- Data fitness, governance, and deployment boundaries must be established for each engagement.
Authoritative references
Sources and method notes
- National Institute of Standards and Technology: AI Risk Management Framework
Voluntary framework for managing AI risk, roles, and accountability. Accessed August 19, 2026.