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Isaca AAIA Practice Test 32

Question 310

An independent AI auditor reviews this case: A hospital uses a cloud embedding service whose disaster recovery copies are placed outside approved jurisdictions. Which TWO complementary elements should the auditor seek: an effective corrective control and the most probative independent evidence? Select TWO answers.

  1. Inspect region endpoints, service architecture, contractual transfer mechanisms, subprocessor lists and logs.
  2. Test whether less identifying features or on-premises transformations satisfy the business purpose.
  3. Inspect use-case criticality, model comparison, reason-code fidelity, feature lineage, adverse-decision samples and appeal test results.
  4. Infer that data stays local solely from the vendor's billing address or local user interface.
  5. Map international processing locations and lawful transfer safeguards through vendors, subprocessors and backups.

Explanation

Correct Answers

A:

The reason it is necessary is: Model prompts, embeddings, logs and training datasets can be transferred even when the front-end appears local. In this case: A hospital uses a cloud embedding service whose disaster recovery copies are placed outside approved jurisdictions.

E:

The reason it is necessary is: Model prompts, embeddings, logs and training datasets can be transferred even when the front-end appears local. This response fits the risk associated with Cross-border AI data transfer mapping: Map international processing locations and lawful transfer safeguards through vendors, subprocessors and backups.

Incorrect Answers

B:

This option concerns Privacy by design for model features, which is a related but different AI governance concern. It does not establish control effectiveness for Cross-border AI data transfer mapping.

C:

This option concerns Explainable credit-model selection for adverse decisions, which is a related but different AI governance concern. For this situation: A hospital uses a cloud embedding service whose disaster recovery copies are placed outside approved jurisdictions.

D:

This attractive shortcut does not resolve the Cross-border AI data transfer mapping weakness: Infer that data stays local solely from the vendor's billing address or local user interface. For this situation: A hospital uses a cloud embedding service whose disaster recovery copies are placed outside approved jurisdictions.

Question 311

A governance and assurance review uncovers the following: A hospital uses a cloud embedding service whose disaster recovery copies are placed outside approved jurisdictions. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.

  1. Inspect region endpoints, service architecture, contractual transfer mechanisms, subprocessor lists and logs.
  2. Inspect notices, collection purposes, privacy review, access approvals, lineage and training-set membership.
  3. Infer that data stays local solely from the vendor's billing address or local user interface.
  4. Compare use-case requirements, deterministic baselines, quantitative error rates, grounded outputs and exception handling.

Explanation

Correct Answer

A:

The reason it is necessary is: Model prompts, embeddings, logs and training datasets can be transferred even when the front-end appears local. For this situation: A hospital uses a cloud embedding service whose disaster recovery copies are placed outside approved jurisdictions.

Incorrect Answers

B:

This option concerns Purpose limitation in AI training data reuse, which is a related but different AI governance concern. The audit must corroborate: Inspect region endpoints, service architecture, contractual transfer mechanisms, subprocessor lists and logs.

C:

For this situation: A hospital uses a cloud embedding service whose disaster recovery copies are placed outside approved jurisdictions.

D:

This option concerns Predictive versus generative model task fit, which is a related but different AI governance concern. The audit must corroborate: Inspect region endpoints, service architecture, contractual transfer mechanisms, subprocessor lists and logs.

Question 312

A risk-based audit engagement examines this operating condition: A hospital uses a cloud embedding service whose disaster recovery copies are placed outside approved jurisdictions. After management addresses the issue, which result MOST convincingly demonstrates effective remediation? Select ONE best answer.

  1. Selected components meet task-specific accuracy, controllability and auditability tests on representative work.
  2. All material flows remain in approved places or have current transfer assessments and safeguards.
  3. Infer that data stays local solely from the vendor's billing address or local user interface.
  4. Validated reduced-data features meet model purpose without exposing unnecessary identities or content.

Explanation

Correct Answer

B:

This is an observable validation result for Cross-border AI data transfer mapping, not just management assurance: All material flows remain in approved places or have current transfer assessments and safeguards.

Incorrect Answers

A:

This option concerns Predictive versus generative model task fit, which is a related but different AI governance concern. For this situation: A hospital uses a cloud embedding service whose disaster recovery copies are placed outside approved jurisdictions.

C:

The auditor should instead examine: Inspect region endpoints, service architecture, contractual transfer mechanisms, subprocessor lists and logs.

D:

This option concerns Privacy by design for model features, which is a related but different AI governance concern. The decisive principle here is: Model prompts, embeddings, logs and training datasets can be transferred even when the front-end appears local.

Question 313

An audit committee asks for a defensible assessment of this situation: A retailer encodes full birth dates and residential addresses although age range and area category meet prediction needs. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.

  1. Validate intended secondary use against lawful basis, original purposes and documented governance before training.
  2. Test whether less identifying features or on-premises transformations satisfy the business purpose.
  3. Match the model family to the task, retain deterministic calculations where appropriate and validate generative outputs against trusted data and human review.
  4. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.

Explanation

Correct Answer

B:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. The acceptable verified outcome is: Validated reduced-data features meet model purpose without exposing unnecessary identities or content.

Incorrect Answers

A:

This option concerns Purpose limitation in AI training data reuse, which is a related but different AI governance concern. It does not establish control effectiveness for Privacy by design for model features.

C:

This option concerns Predictive versus generative model task fit, which is a related but different AI governance concern. It does not establish control effectiveness for Privacy by design for model features.

D:

This attractive shortcut does not resolve the Privacy by design for model features weakness: Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.

Question 314

During an AI controls assessment, the team learns that a retailer encodes full birth dates and residential addresses although age range and area category meet prediction needs. Which principle BEST explains why the observed practice is a material governance or control concern? Select ONE best answer.

  1. Privacy by design changes processing architecture rather than relying solely on downstream access policy.
  2. Data minimization reduces privacy exposure at input, storage, retrieval and telemetry stages.
  3. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  4. Model prompts, embeddings, logs and training datasets can be transferred even when the front-end appears local.

Explanation

Correct Answer

A:

The acceptable verified outcome is: Validated reduced-data features meet model purpose without exposing unnecessary identities or content. In this case: A retailer encodes full birth dates and residential addresses although age range and area category meet prediction needs.

Incorrect Answers

B:

This option concerns Data minimization and PII in prompts, which is a related but different AI governance concern. It does not establish control effectiveness for Privacy by design for model features.

C:

This attractive shortcut does not resolve the Privacy by design for model features weakness: Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever. For this situation: A retailer encodes full birth dates and residential addresses although age range and area category meet prediction needs.

D:

This option concerns Cross-border AI data transfer mapping, which is a related but different AI governance concern. It does not establish control effectiveness for Privacy by design for model features.

Question 315

An independent AI auditor reviews this case: A retailer encodes full birth dates and residential addresses although age range and area category meet prediction needs. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.

  1. Sample user interface, override permissions, time pressure, rationale records and actual reviewer interventions.
  2. Inspect region endpoints, service architecture, contractual transfer mechanisms, subprocessor lists and logs.
  3. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  4. Compare feature necessity, identifiability, model utility, transformation design and data retention.

Explanation

Correct Answer

D:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. In this case: A retailer encodes full birth dates and residential addresses although age range and area category meet prediction needs.

Incorrect Answers

A:

This option concerns Human oversight design for high-impact AI, which is a related but different AI governance concern. It does not establish control effectiveness for Privacy by design for model features.

B:

This option concerns Cross-border AI data transfer mapping, which is a related but different AI governance concern. For this situation: A retailer encodes full birth dates and residential addresses although age range and area category meet prediction needs.

C:

This attractive shortcut does not resolve the Privacy by design for model features weakness: Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever. The auditor should instead examine: Compare feature necessity, identifiability, model utility, transformation design and data retention.

Question 316

A governance and assurance review uncovers the following: A retailer encodes full birth dates and residential addresses although age range and area category meet prediction needs. After management addresses the issue, which result MOST convincingly demonstrates effective remediation? Select ONE best answer.

  1. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  2. Selected components meet task-specific accuracy, controllability and auditability tests on representative work.
  3. Validated reduced-data features meet model purpose without exposing unnecessary identities or content.
  4. Deletion requests remove or appropriately constrain applicable copies within documented policy and legal requirements.

Explanation

Correct Answer

C:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. This is an observable validation result for Privacy by design for model features, not just management assurance: Validated reduced-data features meet model purpose without exposing unnecessary identities or content.

Incorrect Answers

A:

This attractive shortcut does not resolve the Privacy by design for model features weakness: Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever. Effective closure requires: Validated reduced-data features meet model purpose without exposing unnecessary identities or content.

B:

This option concerns Predictive versus generative model task fit, which is a related but different AI governance concern. For this situation: A retailer encodes full birth dates and residential addresses although age range and area category meet prediction needs.

D:

This option concerns AI inference retention and right-to-erasure handling, which is a related but different AI governance concern. It does not establish control effectiveness for Privacy by design for model features.

Question 317

A risk-based audit engagement examines this operating condition: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation. What is the MOST appropriate risk-based audit recommendation that addresses the root control weakness? Select ONE best answer.

  1. Test whether less identifying features or on-premises transformations satisfy the business purpose.
  2. Design usable human review with understandable context, authority to intervene, escalation and traceable decisions.
  3. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  4. Conduct a documented impact assessment of purpose, necessity, proportionality, alternatives and safeguards before deployment.

Explanation

Correct Answer

A:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. This is the proportionate control response to Privacy by design for model features: Test whether less identifying features or on-premises transformations satisfy the business purpose.

Incorrect Answers

B:

This option concerns Human oversight design for high-impact AI, which is a related but different AI governance concern. The decisive principle here is: Privacy by design changes processing architecture rather than relying solely on downstream access policy.

C:

This attractive shortcut does not resolve the Privacy by design for model features weakness: Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever. In this case: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation.

D:

This option concerns Privacy impact assessment for biometric AI, which is a related but different AI governance concern. It does not establish control effectiveness for Privacy by design for model features.

Question 318

An audit committee asks for a defensible assessment of this situation: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation. Which principle BEST explains why the observed practice is a material governance or control concern? Select ONE best answer.

  1. Privacy by design changes processing architecture rather than relying solely on downstream access policy.
  2. Availability of data inside a company does not imply every new AI training purpose is authorized.
  3. Contractual no-training promises do not address independent log retention, indexing or deletion obligations.
  4. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.

Explanation

Correct Answer

A:

The acceptable verified outcome is: Validated reduced-data features meet model purpose without exposing unnecessary identities or content. Independent audit evidence includes: Compare feature necessity, identifiability, model utility, transformation design and data retention.

Incorrect Answers

B:

This option concerns Purpose limitation in AI training data reuse, which is a related but different AI governance concern. The decisive principle here is: Privacy by design changes processing architecture rather than relying solely on downstream access policy.

C:

This option concerns AI inference retention and right-to-erasure handling, which is a related but different AI governance concern. The decisive principle here is: Privacy by design changes processing architecture rather than relying solely on downstream access policy.

D:

This attractive shortcut does not resolve the Privacy by design for model features weakness: Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever. For this situation: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation.

Question 319

During an AI controls assessment, the team learns that an insurer retains raw call audio for prediction despite a validated nonidentifying feature representation. What evidence should the auditor examine FIRST to substantiate or challenge the control owner’s claim? Select ONE best answer.

  1. Compare feature necessity, identifiability, model utility, transformation design and data retention.
  2. Compare use-case requirements, deterministic baselines, quantitative error rates, grounded outputs and exception handling.
  3. Sample user interface, override permissions, time pressure, rationale records and actual reviewer interventions.
  4. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.

Explanation

Correct Answer

A:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. This evidence directly tests the asserted control for Privacy by design for model features: Compare feature necessity, identifiability, model utility, transformation design and data retention.

Incorrect Answers

B:

This option concerns Predictive versus generative model task fit, which is a related but different AI governance concern. The decisive principle here is: Privacy by design changes processing architecture rather than relying solely on downstream access policy.

C:

This option concerns Human oversight design for high-impact AI, which is a related but different AI governance concern. For this situation: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation.

D:

This attractive shortcut does not resolve the Privacy by design for model features weakness: Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever. Test whether less identifying features or on-premises transformations satisfy the business purpose.

Question 320

An independent AI auditor reviews this case: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation. Which TWO complementary elements should the auditor seek: an effective corrective control and the most probative independent evidence? Select TWO answers.

  1. Design usable human review with understandable context, authority to intervene, escalation and traceable decisions.
  2. Compare use-case requirements, deterministic baselines, quantitative error rates, grounded outputs and exception handling.
  3. Assume pseudonymized identifiers are anonymous and keep unneeded raw attributes forever.
  4. Compare feature necessity, identifiability, model utility, transformation design and data retention.
  5. Test whether less identifying features or on-premises transformations satisfy the business purpose.

Explanation

Correct Answers

D:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. For this situation: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation.

E:

The reason it is necessary is: Privacy by design changes processing architecture rather than relying solely on downstream access policy. This response fits the risk associated with Privacy by design for model features: Test whether less identifying features or on-premises transformations satisfy the business purpose.

Incorrect Answers

A:

This option concerns Human oversight design for high-impact AI, which is a related but different AI governance concern. The audit must corroborate: Compare feature necessity, identifiability, model utility, transformation design and data retention.

B:

This option concerns Predictive versus generative model task fit, which is a related but different AI governance concern. For this situation: An insurer retains raw call audio for prediction despite a validated nonidentifying feature representation.

C:

It misses the key control principle: Privacy by design changes processing architecture rather than relying solely on downstream access policy.

ISACA Advanced in AI Audit (AAIA) Practice Tests