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Isaca AAIA Practice Test 60

Question 590

An independent AI auditor reviews this case: A bank deploys a new classifier to all customers after testing only one branch and later discovers disparate denials. Which TWO complementary elements should the auditor seek: an effective corrective control and the most probative independent evidence? Select TWO answers.

  1. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  2. Use risk-aware canary populations, guardrail metrics, stop criteria and tested rollback or kill switch.
  3. Quarantine suspicious inputs and models, preserve provenance, revert to validated artifacts and investigate contamination.
  4. Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.
  5. Compare before-after distributions, update artifacts, critical use cases, approval rules and rollback records.

Explanation

Correct Answers

B:

The reason it is necessary is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined. For this situation: A bank deploys a new classifier to all customers after testing only one branch and later discovers disparate denials.

D:

The reason it is necessary is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined. The corrective action is: Use risk-aware canary populations, guardrail metrics, stop criteria and tested rollback or kill switch.

Incorrect Answers

A:

This attractive shortcut does not resolve the Canary releases and model rollback thresholds weakness: Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored. For this situation: A bank deploys a new classifier to all customers after testing only one branch and later discovers disparate denials.

C:

This option concerns Model poisoning incident response and rollback, which is a related but different AI governance concern. It does not establish control effectiveness for Canary releases and model rollback thresholds.

E:

This option concerns Model version change impact classification, which is a related but different AI governance concern. For this situation: A bank deploys a new classifier to all customers after testing only one branch and later discovers disparate denials.

Question 591

A governance and assurance review uncovers the following: A bank deploys a new classifier to all customers after testing only one branch and later discovers disparate denials. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.

  1. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  2. Compare provider release notes, model ID, output baselines, contractual notices and drift alerts.
  3. Inspect prompt history, version diffs, tested attack cases, tool allowlists and release tickets.
  4. Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.

Explanation

Correct Answer

D:

The reason it is necessary is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined. This evidence directly tests the asserted control for Canary releases and model rollback thresholds: Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.

Incorrect Answers

A:

This attractive shortcut does not resolve the Canary releases and model rollback thresholds weakness: Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored. The auditor should instead examine: Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.

B:

This option concerns External foundation-model update change notices, which is a related but different AI governance concern. For this situation: A bank deploys a new classifier to all customers after testing only one branch and later discovers disparate denials.

C:

This option concerns Prompt template governance and injection-resilience changes, which is a related but different AI governance concern. It does not establish control effectiveness for Canary releases and model rollback thresholds.

Question 592

A risk-based audit engagement examines this operating condition: A bank deploys a new classifier to all customers after testing only one branch and later discovers disparate denials. After management addresses the issue, which result MOST convincingly demonstrates effective remediation? Select ONE best answer.

  1. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  2. Authorized prompt versions perform as specified and fail closed on tested malicious context.
  3. Material external changes are assessed before or promptly after adoption with controlled escalation.
  4. Unacceptable changes are contained promptly and validated prior behavior is restored.

Explanation

Correct Answer

D:

The reason it is necessary is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined. This is an observable validation result for Canary releases and model rollback thresholds, not just management assurance: Unacceptable changes are contained promptly and validated prior behavior is restored.

Incorrect Answers

A:

This attractive shortcut does not resolve the Canary releases and model rollback thresholds weakness: Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored. Use risk-aware canary populations, guardrail metrics, stop criteria and tested rollback or kill switch.

B:

This option concerns Prompt template governance and injection-resilience changes, which is a related but different AI governance concern. For this situation: A bank deploys a new classifier to all customers after testing only one branch and later discovers disparate denials.

C:

This option concerns External foundation-model update change notices, which is a related but different AI governance concern. The decisive principle here is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

Question 593

An audit committee asks for a defensible assessment of this situation: An AI contact center A/B test has no threshold for stopping an experiment that leaks internal policies. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.

  1. Use risk-aware canary populations, guardrail metrics, stop criteria and tested rollback or kill switch.
  2. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  3. Classify model, data, prompt and feature changes by potential behavior impact and require appropriate regression testing.
  4. Version and trace training, validation and inference datasets with accountable lineage, hashes and reproducible pipeline metadata.

Explanation

Correct Answer

A:

The reason it is necessary is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined. Independent audit evidence includes: Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.

Incorrect Answers

B:

This attractive shortcut does not resolve the Canary releases and model rollback thresholds weakness: Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored. Effective closure requires: Unacceptable changes are contained promptly and validated prior behavior is restored.

C:

This option concerns Model version change impact classification, which is a related but different AI governance concern. The decisive principle here is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

D:

This option concerns AI training dataset lineage and reproducibility, which is a related but different AI governance concern. It does not establish control effectiveness for Canary releases and model rollback thresholds.

Question 594

During an AI controls assessment, the team learns that an AI contact center A/B test has no threshold for stopping an experiment that leaks internal policies. Which principle BEST explains why the observed practice is a material governance or control concern? Select ONE best answer.

  1. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  2. An AI incident ends only after decision impacts, service restoration and recurrence risk are addressed.
  3. AI changes can alter decisions without modifying the application UI or infrastructure code.
  4. Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

Explanation

Correct Answer

D:

The corrective action is: Use risk-aware canary populations, guardrail metrics, stop criteria and tested rollback or kill switch. This is the applicable AI audit principle for Canary releases and model rollback thresholds: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

Incorrect Answers

A:

This attractive shortcut does not resolve the Canary releases and model rollback thresholds weakness: Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored. For this situation: An AI contact center A/B test has no threshold for stopping an experiment that leaks internal policies.

B:

This option concerns AI model rollback and stakeholder communication, which is a related but different AI governance concern. It does not establish control effectiveness for Canary releases and model rollback thresholds.

C:

This option concerns Model version change impact classification, which is a related but different AI governance concern. For this situation: An AI contact center A/B test has no threshold for stopping an experiment that leaks internal policies.

Question 595

An independent AI auditor reviews this case: An AI contact center A/B test has no threshold for stopping an experiment that leaks internal policies. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.

  1. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  2. Compare before-after distributions, update artifacts, critical use cases, approval rules and rollback records.
  3. Inspect impact inventory, rollback record, retesting, business communications and lessons-learned owners.
  4. Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.

Explanation

Correct Answer

D:

The reason it is necessary is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined. In this case: An AI contact center A/B test has no threshold for stopping an experiment that leaks internal policies.

Incorrect Answers

A:

It misses the key control principle: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

B:

This option concerns Model version change impact classification, which is a related but different AI governance concern. The audit must corroborate: Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.

C:

This option concerns AI model rollback and stakeholder communication, which is a related but different AI governance concern. The decisive principle here is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

Question 596

A governance and assurance review uncovers the following: An AI contact center A/B test has no threshold for stopping an experiment that leaks internal policies. After management addresses the issue, which result MOST convincingly demonstrates effective remediation? Select ONE best answer.

  1. Unacceptable changes are contained promptly and validated prior behavior is restored.
  2. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  3. Authorized prompt versions perform as specified and fail closed on tested malicious context.
  4. An independent rerun can identify the exact source data and material transformation decisions for a sampled model version.

Explanation

Correct Answer

A:

This is an observable validation result for Canary releases and model rollback thresholds, not just management assurance: Unacceptable changes are contained promptly and validated prior behavior is restored.

Incorrect Answers

B:

For this situation: An AI contact center A/B test has no threshold for stopping an experiment that leaks internal policies.

C:

This option concerns Prompt template governance and injection-resilience changes, which is a related but different AI governance concern. The decisive principle here is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

D:

This option concerns AI training dataset lineage and reproducibility, which is a related but different AI governance concern. The decisive principle here is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

Question 597

A risk-based audit engagement examines this operating condition: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.

  1. Log emergency AI configuration changes, require proportionate approval, expiry and post-change validation.
  2. Control schema, source, feature and data refreshes using integrity and semantic compatibility tests.
  3. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  4. Use risk-aware canary populations, guardrail metrics, stop criteria and tested rollback or kill switch.

Explanation

Correct Answer

D:

The reason it is necessary is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined. In this case: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

Incorrect Answers

A:

This option concerns AI configuration and emergency change traceability, which is a related but different AI governance concern. It does not establish control effectiveness for Canary releases and model rollback thresholds.

B:

This option concerns AI dataset refresh and feature pipeline approvals, which is a related but different AI governance concern. It does not establish control effectiveness for Canary releases and model rollback thresholds.

C:

This attractive shortcut does not resolve the Canary releases and model rollback thresholds weakness: Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored. In this case: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

Question 598

An audit committee asks for a defensible assessment of this situation: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses. Which principle BEST explains why the observed practice is a material governance or control concern? Select ONE best answer.

  1. An AI incident ends only after decision impacts, service restoration and recurrence risk are addressed.
  2. Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.
  3. AI outputs cannot be audited reliably when their source records, transformations and model lineage cannot be reconstructed.
  4. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.

Explanation

Correct Answer

B:

The corrective action is: Use risk-aware canary populations, guardrail metrics, stop criteria and tested rollback or kill switch. The acceptable verified outcome is: Unacceptable changes are contained promptly and validated prior behavior is restored.

Incorrect Answers

A:

This option concerns AI model rollback and stakeholder communication, which is a related but different AI governance concern. In this case: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

C:

This option concerns AI training dataset lineage and reproducibility, which is a related but different AI governance concern. In this case: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

D:

This attractive shortcut does not resolve the Canary releases and model rollback thresholds weakness: Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored. For this situation: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

Question 599

During an AI controls assessment, the team learns that an online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.

  1. Inspect source contracts, schema diffs, baseline distributions, feature tests and observed scoring changes.
  2. Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.
  3. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  4. Compare provider release notes, model ID, output baselines, contractual notices and drift alerts.

Explanation

Correct Answer

B:

The corrective action is: Use risk-aware canary populations, guardrail metrics, stop criteria and tested rollback or kill switch.

Incorrect Answers

A:

This option concerns AI dataset refresh and feature pipeline approvals, which is a related but different AI governance concern. For this situation: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

C:

For this situation: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

D:

This option concerns External foundation-model update change notices, which is a related but different AI governance concern. In this case: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

Question 600

An independent AI auditor reviews this case: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses. Which THREE elements together provide a defensible AI audit conclusion: the corrective control, the evidence to test it, and a verified outcome? Select THREE answers.

  1. Use risk-aware canary populations, guardrail metrics, stop criteria and tested rollback or kill switch.
  2. Inspect ingestion bursts, source identities, dataset hashes, registry links and clean restore evidence.
  3. Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.
  4. Control schema, source, feature and data refreshes using integrity and semantic compatibility tests.
  5. Call a deployment canary controlled when traffic fraction is small but no adverse-impact trigger is monitored.
  6. Unacceptable changes are contained promptly and validated prior behavior is restored.

Explanation

Correct Answers

A:

The reason it is necessary is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined. For this situation: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

C:

The acceptable verified outcome is: Unacceptable changes are contained promptly and validated prior behavior is restored.

F:

In this case: An online insurer's model rollout lacks a known-good rollback artifact when conversion quality collapses.

Incorrect Answers

B:

This option concerns Model poisoning incident response and rollback, which is a related but different AI governance concern. The decisive principle here is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

D:

This option concerns AI dataset refresh and feature pipeline approvals, which is a related but different AI governance concern. The decisive principle here is: Gradual deployment reduces blast radius only if meaningful indicators and rollback decisions are predefined.

E:

The auditor should instead examine: Inspect canary assignment, segment KPIs, error thresholds, baseline model artifacts and rollback drill.

ISACA Advanced in AI Audit (AAIA) Practice Tests