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AI governance

Permission before automation

meUus AI architecture becomes safer only when status, consent, data permission, tool permission, human confirmation, verification, audit, fallback, and kill switches sit above model capability.

The orchestration chain

User intent → context → orchestrator → policy check → agent selection → data permission → tool permission → human confirmation when required → action → verification → audit. Agents do not receive unlimited access merely because they belong to one ecosystem.

L0–L5 human approval ceiling

L0 Observe/Read. L1 Recommend. L2 Prepare drafts/plans. L3 executes only low-risk reversible actions when policy specifically allows it. L4 consequential actions require human confirmation. L5 is restricted to human/admin/qualified-professional authority for professional judgment, clinical decisions, high-risk financial authority, irreversible destructive action, and sensitive administration.

Classification does not grant permission

An approval level is a ceiling, not an authorization token. A workflow still needs a specific allowed purpose, owner authority, data scope, tool scope, status, risk decision, and evidence that the action is appropriate.

Every AI system needs a contract

Minimum record: AI ID/name/version, purpose, owner, status, allowed actions, prohibited actions, data access, memory access, tool access, source policy, model/provider, fallback, human/professional review requirement, risk classification, logging/retention, kill switch, public status, evaluation/test set, last review, and evidence.

Event does not equal permission

An event may request a workflow; policy decides whether it may proceed. A service request, profile change, overdue task, or expired evidence may trigger checking and preparation, but not free autonomous action.

Verification and safe failure

Meaningful execution should end in result → evidence → verify → accept/correct → learn. Consequential AI/automation must be disable-able. Fallback may be deterministic/manual flow, queued human review, provider fallback, correction + audit, output blocking, rollback, or retained request + notification.

Reflection

Questions to sit with

  1. What approval level is this action, and who actually owns the authority?
  2. What exact data and tool permissions are necessary—nothing more?
  3. How can the action be verified, corrected, rolled back, or stopped?

One safe next action

For any proposed AI automation, write: purpose, allowed data, allowed tools, approval level, verification method, safe fallback.