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  1. Home
  2. ISACA Certification
  3. AAIA Exam
  4. ISACA.AAIA.v2026-06-21.q153 Dumps
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Question 1

When auditing AI systems, which data management practice BEST ensures compliance with privacy regulations?

Correct Answer: B
Privacy regulations like GDPR and CCPA emphasize the principle of " Data Minimization " -collecting only the data that is strictly necessary for the intended purpose. In an AI context, organizations often feel tempted to collect as much data as possible to improve accuracy (Option A), but this increases privacy risk and legal exposure. According to ISACA, implementing data minimization is the most effective practice for ensuring regulatory compliance. It reduces the " attack surface " in the event of a breach and ensures that the organization is not holding onto sensitive PII that it cannot justify. Indefinite retention (Option D) is a direct violation of most modern privacy laws.
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Question 2

An IS auditor is reviewing a dataset used by a university to train a predictive machine learning model. Which of the following MOST likely indicates risk that the model could not process all data and make necessary correlations?

Correct Answer: C
A numeric field stored as an object (string) format (option C) indicates improper data typing.
Models cannot correctly compute correlations or statistical relationships when numerical values are stored as textual data.
AAIA emphasizes that incorrect datatypes are one of the most common causes of ML model misbehavior, including:
Failure to compute averages, correlations, or mathematical operations
Silent errors in preprocessing
Skewed learning patterns
Incorrect feature importance evaluations
Thus, the Final Grade Percent field in object format is the most significant indicator of processing risk.
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Question 3

Which of the following is the BEST recommendation for an organization that has adopted "vibe coding" (using AI to generate code based on high-level natural language prompts)?

Correct Answer: B
"Vibe coding" or AI-assisted development carries the risk of introducing "hallucinated" vulnerabilities or insecure coding patterns that the AI learned from public (and potentially flawed) repositories. The most responsible control is to implement a rigorous, human-led "security checklist" for code reviews. This ensures that every line of AI-generated code is checked for common flaws like SQL injection or hardcoded credentials.
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Question 4

Which of the following is the PRIMARY objective of performing adversarial testing on AI models?

Correct Answer: D
Adversarial testing involves simulating real-world attacks or malicious inputs against AI models (e.g., adversarial examples, poisoning, evasion) to identify how the system behaves under intentional misuse or hostile conditions. The primary objective is to discover weaknesses and control gaps (D) in the model and its surrounding processes--such as inadequate input validation, insufficient monitoring, or missing safeguards against adversarial inputs.
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Question 5

Which use case for an AI model to be used by a food delivery service would pose ethical risk to the organization?

Correct Answer: B
Using AI to make employment decisions such as driver termination or retention introduces significant ethical risks. If based solely on performance metrics without context or human review, such systems can lead to unfair treatment or discrimination-violating principles of transparency and due process.
"Automating workforce decisions must be approached cautiously to prevent discriminatory outcomes. Ethical AI governance requires oversight when AI is used for employment-impacting decisions." A, C, and D involve business optimization without directly affecting individual employment rights. Therefore, B poses the greatest ethical risk.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Human Impact and Workforce Automation Ethics"
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