Academy module 7 · ISO/IEC 42001 · Lesson 7 of 8
Monitor performance and control AI changes
About 12 minutes · Introductory draft · Checked 2026-10-24
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Picture the topic
Remember this: Watch outcomes and context, not just whether the endpoint is online.
Explore the anchors
Monitor relevant performance incidents and feedback.
Concept matching activity
Match this task or description to its concept:
Interpret changes against intended use and limits.
Choose a concept before checking the explanation.
Detection laboratory
Positive means the detector raised an alert. True/false compares that decision with known reality.
False negative — An attack exists. No alert was raised.
| Detector | Attack present | No attack |
|---|---|---|
| Alert | True positive | False positive |
| No alert | False negative | True negative |
Change the threshold
Eight fictional events have fixed known truth. An alert fires when the synthetic score is at least the threshold. The score is not a probability of attack.
TP 2 · FP 1 · FN 2 · TN 3. Precision 67%. Recall 50%.
Precision = TP ÷ (TP + FP). Recall = TP ÷ (TP + FN). Lower thresholds can increase detection and false alarms; this tiny dataset does not establish real-world performance.
A quick way to study this topic
- Hide the explanation and redraw these three anchors from memory.
- Explain the difference between the anchors in your own words.
- Apply the distinction to the worked example below. Check the full lesson for assumptions and exceptions.
- Recall it again tomorrow, then after a few days. A memory hint is a retrieval cue, not a replacement for understanding.
Original academy illustrations and fictional exercises. These are learning simulations, not a real virtual machine, network assessment or measure of job readiness. Activities reset when you leave or reload; they do not change quiz scores.
What you will learn
- Monitor relevant performance incidents and feedback.
- Interpret changes against intended use and limits.
- Authorize investigation restriction or revalidation.
Concepts and distinctions
AI-system monitoring should reflect intended outcomes, relevant groups, input conditions and operating limits. Technical availability is one signal; a reachable endpoint can still produce unsuitable results. Changes in input distribution, feedback processes or model service behavior may justify investigation even when average system metrics look stable.
Distinguish security incidents, performance problems and other adverse impacts while maintaining routes for coordinated response. One observation may support several hypotheses and should not be forced prematurely into a single category. Protect relevant evidence, apply appropriate privacy handling and involve the people who own data, models, operations and the affected business use.
Apply the process and collect evidence
Define thresholds and review responsibilities before launch. Record changes to models, data, configuration and purpose, then determine what revalidation or approval is needed. Use feedback to identify patterns without treating every complaint as proof of a specific defect. Escalate consequential concerns and validate the outcome of corrective actions before concluding the system is back within acceptable conditions.
Findings, documentation quality and closing the audit
A nonconformity report should connect an applicable requirement, identified evidence and a precise statement of the gap. For example, if the organization requires impact reassessment before a material use change, document the changed use, sampled approval records and missing assessment. Do not invent an ISO clause number from a training slide. Distinguish confirmed facts, reasonable inferences and matters needing further investigation.
Quality review checks that conclusions follow the workpapers, classifications follow agreed rules and limitations remain visible. Control the report’s versions, recipients, archival access and retention. At closing, review objectives achieved, findings, unresolved disagreements, action expectations and next steps. Closure communicates supported results and agreed next steps; it does not conceal unresolved limitations.
Work through a scenario
Fictional facts for learning. This exercise is not scored.
A support assistant remains online but begins giving poorer responses to a newly introduced product line. Operations reports the system healthy because uptime is unchanged.
Compare your reasoning
Investigate performance for the changed use and relevant data rather than relying only on uptime. Identify version and context changes, apply interim review or restrictions if needed, and authorize appropriate revalidation before expanding use further.
Remember
- Watch outcomes and context, not just whether the endpoint is online.
- Monitor relevant performance incidents and feedback.
- Authorize investigation restriction or revalidation.
Orientation and further reading
Original examples and explanations. Background references do not establish complete exam coverage.
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