Synthetic authenticity asks when an AI should be allowed to act in a role that matters. The framework helps leaders set limits, assign responsibility and protect trust as the AI changes.
What can this AI do, who is it acting for and who is responsible?
The more authority it has, the stronger the permission it needs.
Inform
Recommend
Decide
Transact
Commit
Version threshold
A change to the model, memory, rules or owner can create a meaningfully different AI.
Can we identify the exact version that acted and what changed?
Authority ceiling
The most an AI may do without fresh human approval.
Can we state what it may do alone and when a person must step in?
Reliance exposure
How much people, institutions or markets depend on the AI and carry the risk of its actions.
Can we see who relies on it, who it represents and who bears the risk?
Recourse window
The time and route people have to challenge, correct or reverse an AI-mediated outcome.
Can someone get an explanation, correction and accountable human response in time?
Legitimacy gapThe gap opens when an AI can do more than it has been given permission to do.
Review its permission when the model, memory, role, people it serves or stakes change.
Institutional trust grows when what AI can do, what it may do and who answers for it stay aligned.
