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| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | ISACA Advanced in AI Audit (AAIA) Exam |
| Exam Number: | AAIA |
| Passing Score: | 65% |
| Available Languages: | English |
| Related Certifications: | CISA CPA CIA |
| Exam Price: | USD 459 (member), USD 599 (non-member) |
| Exam Format: | Computer-based, Closed-book, Remote proctoring or test center, Multiple-choice |
| Exam Duration: | 120 minutes |
| Certificate Validity Period: | Not publicly specified (requires ongoing CPE maintenance after certification) |
| Real Exam Qty: | 55 |
| Recommended Training: | Official AAIA Training Course Providers ISACA AI Audit Training Resources |
| Exam Registration: | ISACA AAIA Certification Page |
| Sample Questions: | ISACA AAIA Sample Questions |
| Exam Way: | Computer-based exam delivered via PSI test centers or remote proctoring |
| Pre Condition: | Must hold an active CISA, CIA, CPA, or equivalent ISACA-approved advanced auditing certification |
| Official Syllabus URL: | https://www.isaca.org/credentialing/aaia |
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NEW QUESTION # 166
An organization's AI model used in the recruitment screening process was found to favor one gender of candidates over others. It was noted that the AI model was trained on recruitment records where the majority of new hires were male. Which bias would this BEST demonstrate?
Answer: A
Explanation:
"Historical Bias" occurs when the training data reflects existing social prejudices or past inequalities. If an organization's historical hiring practices favored males, an AI model trained on those records will "learn" that being male is a characteristic of a successful candidate. This automates and perpetuates past discrimination into future decisions. The AAIATM manual emphasizes that auditors must evaluate training data for historical bias to ensure fairness. Unlike confirmation bias (which involves seeking data that supports existing beliefs) or label bias (which involves incorrect classification), historical bias is a systemic issue inherent in the data collection from a flawed real-world environment.
NEW QUESTION # 167
Which of the following BEST describes the purpose of a "model validation" function that is independent from the model development team?
Answer: A
Explanation:
Independent model validation mirrors the "second line of defense" concept in risk management -- separating those who build the model from those who challenge and approve it reduces conflict of interest and confirmation bias.
NEW QUESTION # 168
Which control is MOST important to verify in order to ensure proper data management with AI systems?
Answer: C
Explanation:
According to the ISACA AAIATM Study Guide, a "Data Governance Framework" is the foundational control. It provides the policies, roles (stewards, owners), and standards necessary to manage the entire data lifecycle. Without a framework, activities like inventorying (Option C) or labeling (Option D) are ad-hoc and lack accountability. A formal framework ensures that data management is consistent, compliant with privacy laws, and aligned with the organization's risk tolerance. It is the "enabling" control that makes all other data quality and security metrics meaningful and enforceable.
NEW QUESTION # 169
Which of the following initially provides assurance that the developer correctly interprets and identifies numerical data for balancing prior to inserting into the model?
Answer: B
Explanation:
A data dictionary (A) is the authoritative source for understanding:
Data types and numeric formats
Valid ranges and interpretations
Field definitions and business meaning
Normalization and scaling expectations
Before balancing or preprocessing data, developers must verify that they understand each feature correctly. The AAIA framework emphasizes that misinterpretation of numeric variables often leads to:
Incorrect normalization
Faulty scaling
Skewed class balancing
Inaccurate model training
NEW QUESTION # 170
An organization plans to share customer data collected through an AI system with third-party vendors. Which of the following BEST demonstrates compliance with data privacy principles?
Answer: D
Explanation:
The strongest demonstration of compliance with privacy principles--especially those emphasized in AAIA, such as lawfulness, transparency, and consent--is obtaining expressed customer consent (B) before sharing data with third parties. Consent ensures that data processing aligns with legal and ethical requirements, reducing risks related to regulatory violations, unauthorized processing, and loss of customer trust.
NEW QUESTION # 171
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