AAIA認定資格試験、AAIA受験練習参考書

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ISACA AAIA Exam Overview:

Certification Vendor:	ISACA
Exam Name:	ISACA Advanced in AI Audit
Exam Number:	AAIA
Available Languages:	English
Exam Format:	Multiple Choice, Remotely Proctored, Computer-Based
Related Certifications:	CISA FCCA ACCA CIA CPA
Real Exam Qty:	90
Exam Duration:	120 minutes
Passing Score:	65%
Sample Questions:	ISACA AAIA Sample Questions
Exam Way:	Online remotely proctored computer-based exam
Pre Condition:	Candidates must hold an active CISA certification or another qualified audit-related designation such as CIA, CPA, ACCA, FCCA, Canadian CPA, Australian CPA/FCPA, or Japanese CPA.
Official Syllabus URL:	https://www.isaca.org/credentialing/aaia

>> AAIA認定資格試験 <<

AAIA受験練習参考書、AAIA対応受験

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ISACA AAIA 認定試験の出題範囲：

トピック	出題範囲
トピック 1	AI GOVERNANCE AND RISK: It encompasses understanding different AI models and their life cycles, guiding AI strategy, defining roles and policies, managing AI-related risks, overseeing data privacy and governance, and ensuring adherence to ethical practices, standards, and regulations.
トピック 2	AI Operations: It covers managing AI-specific data needs—including collection, quality, security, and classification—applying development lifecycle methodologies with privacy and security by design, change and incident management, testing AI solutions, identifying AI-related threats and vulnerabilities, and supervising AI deployments.
トピック 3	Auditing Tools and Techniques: This section of the exam measures the skills of AI auditors and centers on auditing AI systems using appropriate tools and methods. It includes audit planning and design, sampling methodologies specific to AI, collecting audit evidence, using data analytics for quality assurance, and producing AI audit outputs and reports, including follow-up and quality control measures.

ISACA Advanced in AI Audit 認定 AAIA 試験問題 (Q117-Q122):

質問 # 117
Which of the following is the MOST important risk for an IS auditor to consider when reviewing the adoption of an AI system?

A. Bias in AI system decision making
B. Costs associated with AI system maintenance
C. Resistance to the use of AI technology
D. Immaturity of AI systems in the industry

正解：A

解説：
Bias in AI decision-making is one of the most critical risks, particularly when AI influences areas like hiring, lending, or healthcare. The AAIA™ Study Guide highlights the ethical and operational consequences of biased models, which may lead to discrimination, legal liability, and reputational damage.
"Bias in AI outputs can originate from skewed training data or flawed algorithms. Auditors must evaluate whether mitigation techniques, such as bias detection and fairness testing, are in place." While costs (A) and industry maturity (B) are considerations, they do not pose the same systemic ethical risk.
Resistance (D) is a change management issue. C represents the most impactful and widespread risk.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Bias and Fairness in AI"

質問 # 118
Which of the following should be of GREATEST concern to an IS auditor when reviewing ethical considerations for an AI solution?

A. The solution is hosted on a shared cloud environment.
B. The solution documentation is still in draft.
C. The model has not been retrained recently.
D. The decision-making process is unexplainable.

正解：D

解説：
TheGREATEST concernis when the AI system'sdecision-making process is unexplainable(A), especially for high-impact or regulated decisions. AAIA stresses that explainability is essential for accountability, fairness assessments, compliance, and public trust. If decisions cannot be explained, the organization cannot validate fairness, detect bias, or justify outcomes to regulators or affected individuals.
Cloud hosting (B) is manageable through standard controls. Retraining frequency (C) affects performance but not core ethics. Draft documentation (D) is a procedural issue, not an ethical barrier. Unexplainable decision logic is thefoundational ethical risk.
References:
ISACA,AAIA Exam Content Outline- Domain 5: Ethical and Legal Considerations in AI (explainability, accountability).

質問 # 119
An organization deploys an AI recruitment platform to screen job applicants. The IS auditor identifies that the platform's decisions may be influenced by model bias. Which of the following risk mitigation strategies is BEST for the auditor to recommend?

A. Suspend the use of the AI system until the training data can be verified for fairness and compliance.
B. Retrain the AI model using an external data set certified for inclusivity and fairness.
C. Require manual reviews of all AI-generated recruitment decisions before hiring is finalized.
D. Implement a process to periodically test the AI system for biases and adjust parameters as needed.

正解：D

質問 # 120
An organization using AI to create digital content faces challenges in protecting its intellectual property.
Which of the following is the BEST way to mitigate this risk?

A. Apply adversarial training.
B. Implement a firewall.
C. Separate training and production data.
D. Implement watermarking.

正解：D

解説：
For AI-generated content (images, text, or audio), " watermarking " is a critical technical control to protect Intellectual Property (IP) and ensure provenance. Digital watermarks can be embedded into the metadata or the content itself (often invisibly) to prove the organization is the creator and to track unauthorized distribution. This supports legal claims and brand protection. Firewalls and data separation protect the system , but watermarking protects the output once it is shared online or with clients. As AI makes content creation easier, the ability to prove ownership becomes an essential ethical and legal safeguard.

質問 # 121
An IS auditor is reviewing change documentation of an AI model. Which of the following would pose the GREATEST risk?

A. The seed used for testing is not documented.
B. Management has not tested the model.
C. Test results are not in a standardized format.
D. There is a low number of test scenarios.

正解：D

解説：
A low number of test scenarios (C) indicates insufficient testing coverage, creating a high likelihood that errors, biases, or edge-case failures remain undetected. AI systems require broad, diverse scenario testing, including fairness, robustness, and stress testing. AAIA highlights comprehensive testing as essential to AI reliability and risk mitigation.

質問 # 122
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