Implementation Kit
AI Human Oversight Checklist and Review Decision Template
Designing oversight that is real: a workflow design checklist, a reviewer decision template that captures reasoning on agreement as well as override, a reviewer qualification standard by decision type, and a spec for override-rate monitoring.
Who this is for: The system owner designing or rebuilding the human review step for a high-risk AI decision.
1. Human oversight workflow design checklist
SpreadsheetThe conditions that make review meaningful rather than a rubber stamp.
Template
| Condition | In place? | Note |
|---|---|---|
| Reviewer sees the AI recommendation AND the key factors behind it | Y / N | |
| Reviewer sees at least one alternative or the counterfactual | Y / N | |
| Reviewer has enough time allocated per case for genuine judgment | Y / N | target seconds/minutes |
| Reviewer can access the underlying record, not just the AI summary | Y / N | |
| Reviewer has authority to override without escalation for routine cases | Y / N | |
| The default action is not "accept" on timeout | Y / N | |
| Reviewer is shielded from productivity metrics that punish overrides | Y / N | |
| Reviewer documents reasoning for every decision, agree or override | Y / N |
Worked example
| Condition | In place? | Note |
|---|---|---|
| Sees recommendation + key factors | Y | top-5 features shown |
| Sees an alternative / counterfactual | N | design gap: add "what would change this score" |
| Adequate time per case | N | 45s average; target 3 min for High tier |
| Access to underlying record | Y | one click to the full application |
| Authority to override routine cases | Y | |
| No accept-on-timeout | N | current UI auto-advances after 60s |
| Shielded from override-punishing metrics | N | handle-time target discourages scrutiny |
| Reasoning documented every time | N | only overrides are logged today |
Acceptance criteria
- ✓Every condition is assessed against the live workflow, with gaps listed.
- ✓Time-per-case is a real number measured from logs, compared to a target.
- ✓The workflow does not treat inaction or timeout as approval.
2. Reviewer decision documentation template
SpreadsheetCaptured on every case. Reasoning on agreement matters as much as on override.
Template
| Field | Entry |
|---|---|
| Case / decision ID | |
| AI recommendation and score | |
| Key factors shown to the reviewer | |
| Reviewer decision (accept / override / modify) | |
| Reviewer rationale (required on every decision) | |
| Information the reviewer used beyond the AI summary | |
| Time spent | |
| Reviewer ID and qualification level |
Worked example
| Field | Entry |
|---|---|
| Case ID | dec-2026-0091823 |
| AI recommendation | score 2/5, "advance: no" |
| Key factors shown | low years_experience; medium skill_match |
| Reviewer decision | Override to "advance" |
| Reviewer rationale | Candidate's portfolio shows shipped work the model cannot see; skill match understated |
| Info used beyond summary | opened full application and portfolio link |
| Time spent | 4 min |
| Reviewer ID / level | u-4471, certified recruiter (level 2) |
Acceptance criteria
- ✓A rationale is required and recorded for accept decisions, not only overrides.
- ✓The record captures what the reviewer looked at beyond the AI output.
- ✓Records are retained for the period the underlying decision type requires.
3. Reviewer qualification requirements
SpreadsheetWhat a person must know and hold to review each decision type.
Template
| Decision type | Minimum role / certification | Domain knowledge required | Training on this AI system | Recertification |
|---|---|---|---|---|
| <type> | annual / biennial |
Worked example
| Decision type | Minimum role | Domain knowledge | System training | Recertification |
|---|---|---|---|---|
| Hiring screen override | Certified recruiter L2 | Role requirements; adverse-impact basics | 2h module on the screener's factors and limits | annual |
| Fraud hold release | Fraud analyst L3 | Payment fraud patterns; false-positive cost | 3h module + shadowing | annual |
| Benefits eligibility | Caseworker + supervisor sign-off for denials | Program rules; appeals process | 2h module | biennial |
Acceptance criteria
- ✓Each decision type names a concrete qualification, not "trained staff".
- ✓Reviewers have completed system-specific training on the AI's factors and known limits.
- ✓Qualifications are tracked with expiry dates and recertification.
4. Override-rate monitoring spec
SpreadsheetWhat to measure so a near-zero override rate gets investigated.
Template
| Metric | Definition | Expected range | Investigate when |
|---|---|---|---|
| Overall override rate | overrides / total reviews | <set from a calibration sample> | outside range for 2 weeks |
| Override rate by reviewer | per reviewer | within X points of team median | near zero, or 3x median |
| Time-per-review distribution | median and 10th percentile | 10th pct above a floor | 10th pct near zero |
| Agreement on divergent cases | rate reviewers accept AI when it conflicts with the record | context-specific | trending toward 100% |
| Post-decision reversal rate | decisions later overturned on appeal | low | rising, especially for one reviewer |
Worked example
| Metric | Value this month | Range | Status |
|---|---|---|---|
| Overall override rate | 4% | 8-18% (from calibration) | Investigate: low |
| Lowest reviewer override rate | 0.6% (u-3390) | within 6 pts of 11% median | Investigate |
| 10th-percentile review time | 12s | above 60s floor | Investigate: too fast |
| Appeal reversal rate | 2.1% | under 3% | OK |
| Finding: the low override rate tracks with the 60s auto-advance and the handle-time target. Both flagged to the workflow redesign. |
Acceptance criteria
- ✓Expected ranges come from a calibration exercise, not a guess.
- ✓Per-reviewer rates are monitored, and near-zero rates trigger a review of that reviewer's workload and tooling.
- ✓The dashboard is actually watched, with a named owner and a cadence.
Governance controls this kit produces evidence for
Completing the artifacts above gives you a head start on the evidence requirements for these controls.
The workflow checklist and decision template are the design of the human approval gate for consequential decisions.
The decision documentation template is the output review workflow record.
The qualification requirements artifact is the reviewer competency standard.
The override-rate spec is the automation-bias detection mechanism.
Per-case reviewer decisions and rationale extend decision logging to the human step.
This kit backs one playbook. Read the full guidance for the reasoning behind each artifact.
Decide what to implement next
Assess your governance gaps, then create an action plan with owners and target dates. Build and export without an account; sign in when you want to save your plan.
Start the AI governance assessment →