Safety, privacy, and governance · Lesson 8 of 15 · 6 min

Review approved use

Approved use is specific to the task, data and controls that were reviewed. A new high-impact use needs its own assessment rather than inheriting an unrelated approval.

Open the lab Course map

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learner@clairos:~ $

↑ history · Tab complete · Ctrl+C cancel · Esc, Tab to leaveExit 0

Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-safety-governance-008.json. Separate the recorded facts from your assumptions.
Hint & worked example
Approved use is specific to the task, data and controls that were reviewed. A new high-impact use needs its own assessment rather than inheriting an unrelated approval.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-safety-governance-008.json
```
Common mistake to avoid: Approval for drafting notes covers autonomous decisions too.
2
Isolate the deciding signal
Select the approval_covers_new_task field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Request a separate review for the new eligibility-decision task.
A successful JSON query isolates approval_covers_new_task.
```
jq .approval_covers_new_task /opt/ai-lab/cases/aiops-safety-governance-008.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: request-use-review, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-safety-governance-008-decision.txt.
Hint & worked example
Request a separate review for the new eligibility-decision task.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'request-use-review' > /home/learner/lab/aiops-safety-governance-008-decision.txt
```
Common mistake to avoid: Approval for drafting notes covers autonomous decisions too.

Understand the pattern

Approved use is specific to the task, data and controls that were reviewed. A new high-impact use needs its own assessment rather than inheriting an unrelated approval.

Interpret the evidence

Request a separate review for the new eligibility-decision task.

A tempting mistake

Approval for drafting notes covers autonomous decisions too.

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-008.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "approved_task": "drafting internal notes",
  "new_task": "automatic eligibility decision",
  "approval_covers_new_task": false
}

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

$ jq .approval_covers_new_task /opt/ai-lab/cases/aiops-safety-governance-008.json

false

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

$ printf '%s\n' 'request-use-review' > /home/learner/lab/aiops-safety-governance-008-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 “request-use-review” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Review approved use” justify?Make the change now and gather the missing evidence afterward.Request a separate review for the new eligibility-decision task.Approval for drafting notes covers autonomous decisions too.

Apply it elsewhere

A colleague concludes: “Approval for drafting notes covers autonomous decisions too.” What should you do?Reject that conclusion; return to the case evidence and its stated limits.Accept it because the training command completed.Treat this fixture as a live measurement.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Inspect refusal evidence Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision