Review roles
Assign who can review, escalate, approve, or reject within a workflow.
Definition
What human-in-the-loop means operationally
Human-in-the-loop is more than showing an Approve button after a chat response. Use the HITL governance checklist and an AI decision authority matrix to name roles before go-live. The human override study design explains how review and override rates would be measured from Decision Ledger events.
Operationally, it means defined review roles, escalation paths, decision thresholds, recorded approvals or rejections, and a history of overrides. Retain those outcomes in a Decision Ledger field set.
Controls
Structured authority, not informal oversight
Escalation routes
Move contested or high-impact cases to the appropriate authority.
Decision thresholds
Apply stronger review when risk, disagreement, or uncertainty increases.
Approval and rejection states
Capture explicit outcomes instead of relying on memory or chat scrollback.
Change and override history
Retain how recommendations changed before final authorization.
Named authorization
Preserve who authorized an action-ready decision package.
Limits
Review quality still depends on people and policy
Controls do not substitute for reviewer competence, adequate evidence, or organizational policy. High-accountability programs should also follow a practical federal AI governance implementation sequence when agency or contractor requirements apply.
Inappropriate use includes treating model consensus as automatic approval or using AI outputs as final authority in consequential settings without documented human review. For a product-oriented walkthrough of review gates, see the SmartSolo product demo.
FAQ
Frequently asked questions
Can SmartSolo make consequential decisions on its own?
No. SmartSolo supports analysis and structured review while accountable people retain final authority over consequential decisions.
Is an approval button enough?
Not by itself. Effective human-in-the-loop practice needs roles, thresholds, escalation, and durable records of what was authorized.
Product proof
Human review before authorization
Consensus analysis supporting reviewer scrutiny
What you are seeing: SmartSolo consensus analysis highlighting agreement and conflict across models. Why it matters: disagreement is surfaced for human review rather than treated as automatic truth.
Related
Continue exploring
References
References
Authoritative sources cited for nearby factual claims. Links open official publisher pages.
See governed AI execution in a live workflow
Review how SmartSolo coordinates multiple AI models, routes human authorization, and preserves the decision record.