高質量的AAIA信息資訊和認證考試的領導者材料和免費PDF AAIA考試內容

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ISACA AAIA Exam Syllabus Topics:

SectionObjectives
AI Operations- AI System Lifecycle
  • 1. Configuration and change management
  • 2. Monitoring and maintenance
  • 3. AI system development and deployment
- AI Data Management
  • 1. Training and testing data
  • 2. Data quality and integrity
  • 3. Operational AI controls
AI Governance and Risk- AI Governance Frameworks
  • 1. AI policies and governance structures
  • 2. AI risk management
  • 3. Regulatory and compliance considerations
- AI Security and Controls
  • 1. Vendor and supply chain risk
  • 2. Threat and vulnerability management
  • 3. Identity and access management
AI Auditing Tools and Techniques- Audit Testing and Reporting
  • 1. Testing and sampling methodologies
  • 2. Evidence collection techniques
  • 3. Audit reporting and follow-up
- AI Audit Planning
  • 1. Audit resource planning
  • 2. AI audit methodologies
  • 3. Audit scoping and objectives

>> AAIA信息資訊 <<

最新的ISACA AAIA：ISACA Advanced in AI Audit信息資訊 - 權威的KaoGuTi AAIA考試內容

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最新的 Advanced in AI Audit AAIA 免費考試真題 (Q219-Q224):

問題 #219
Which of the following are the MOST appropriate stages in the AI life cycle for evaluating edge cases?

答案：C

解題說明：
Evaluatingedge cases-rare but critical scenarios where AI may behave unpredictably-must be done during thetest and verifystage (D). This phase is designed to simulate extreme or unusual inputs, validate performance under stress, and ensure robustness and safety before deployment. AAIA highlights that robustness testing, including edge case evaluation, is a key testing technique for AI solutions.
While planning (A) and data collection (C) prepare inputs, they do not evaluate model behavior. Operating and monitoring (B) may detect issues later, but edge case testing must occurpre-deploymentto reduce risk.
References:
ISACA,AAIA Exam Content Outline- Domain 2: Testing Techniques for AI Solutions (edge cases, robustness testing).


問題 #220
An organization's system development process has been enhanced with AI. Which of the following features presents the GREATEST risk?

答案：A

解題說明：
Allowing AI to autonomously generate code without human review introduces significant risks, including security vulnerabilities, logic errors, and noncompliance with organizational development standards. The AAIA™ Study Guide strongly advocates for human-in-the-loop oversight, particularly in automated development contexts.
"AI-assisted development must include manual code reviews to ensure functionality, compliance, and security. Autonomous code generation without validation increases the risk of introducing undetected flaws." While A, B, and C involve operational risks or inefficiencies, only D constitutes a direct breach of secure development life cycle principles.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Fundamentals and Technologies," Subsection: "AI in Software Development and Associated Risks"


問題 #221
The PRIMARY purpose of utilizing neural networks in AI is to:

答案：C


問題 #222
An IS auditor identifies that an AI model occasionally invents nonexistent medical test results. Which of the following recommendations would BEST mitigate this risk?

答案：A

解題說明：
Inventing nonexistent medical test results is a form ofhallucinationcommonly associated with generative AI models.Reducing top-p sampling(A) restricts the model to choosing from the most probable next tokens, reducing randomness and preventing the generation of fabricated or implausible content. AAIA emphasizes configuration tuning (temperature, top-k, top-p) as critical controls for mitigating hallucinations.
Increasing context (B) helps provide more information but does not directly reduce hallucinations. Increasing temperature (C) would make hallucinationsworseby adding randomness. Frequency penalties (D) discourage repetition, not hallucinations. The strongest mitigation isreducing sampling randomnessvia reduced top-p.
References:
ISACA,AAIA Exam Content Outline- Domain 2: AI Operations (generative AI safeguards, hallucination mitigation).


問題 #223
A company deploys a third-party AI vendor's model without visibility into its training data or architecture. What is the PRIMARY audit concern?

答案：C

解題說明：
"Black box" third-party models limit the organization's ability to independently validate fairness, robustness, and explainability -- key AI risk domains -- making vendor due diligence and contractual transparency clauses essential.


問題 #224
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