Safety, privacy, and governance · Lesson 10 of 15 · 8 min

Review human escalation

Human escalation needs an identified recipient, a bounded reason and a safe hold state. A vague “ask someone” message is not an operational handoff.

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learner@clairos:~ $

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-safety-governance-010.json. Separate the recorded facts from your assumptions.
Hint & worked example
Human escalation needs an identified recipient, a bounded reason and a safe hold state. A vague “ask someone” message is not an operational handoff.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-safety-governance-010.json
```
Common mistake to avoid: Execute first and ask for approval afterward.
2
Isolate the deciding signal
Select the review_queue field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Route the case to high-risk-review without executing it automatically.
A successful JSON query isolates review_queue.
```
jq .review_queue /opt/ai-lab/cases/aiops-safety-governance-010.json
```
Common mistake to avoid: Using a different case or an unrelated signal as the justification.
3
Record your operational decision
Choose the justified code: route-human-review, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-safety-governance-010-decision.txt.
Hint & worked example
Route the case to high-risk-review without executing it automatically.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'route-human-review' > /home/learner/lab/aiops-safety-governance-010-decision.txt
```
Common mistake to avoid: Execute first and ask for approval afterward.

Understand the pattern

Human escalation needs an identified recipient, a bounded reason and a safe hold state. A vague “ask someone” message is not an operational handoff.

Interpret the evidence

Route the case to high-risk-review without executing it automatically.

A tempting mistake

Execute first and ask for approval afterward.

All names, measurements, prices, versions, and thresholds in this exercise are fictional training data. The evidence supports this bounded scenario, not a claim about a live provider.

Worked example and expected result

$ cat /opt/ai-lab/cases/aiops-safety-governance-010.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "requires_review": true,
  "review_queue": "high-risk-review",
  "auto_execute": false
}

Exit status: 0. The command completed successfully in the training fixture.

$ jq .review_queue /opt/ai-lab/cases/aiops-safety-governance-010.json

"high-risk-review"

Exit status: 0. The command completed successfully in the training fixture.

$ printf '%s\n' 'route-human-review' > /home/learner/lab/aiops-safety-governance-010-decision.txt

(no output; exit 0)

Exit status: 0. The command completed successfully in the training fixture.

Try a variation

Name the assumption that would have to change for “route-human-review” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Review human escalation” justify?Execute first and ask for approval afterward.Make the change now and gather the missing evidence afterward.Route the case to high-risk-review without executing it automatically.

Apply it elsewhere

A colleague concludes: “Execute first and ask for approval afterward.” What should you do?Treat this fixture as a live measurement.Reject that conclusion; return to the case evidence and its stated limits.Accept it because the training command completed.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Check audit metadata Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision