AAIA資格復習テキスト & AAIA認定試験

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ISACA AAIA Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Governance and Risk	33%	- AI Models, Considerations, and Requirements - AI Risk Management - AI Governance and Program Management - Ethics, Regulations, and Standards for AI - Privacy and Data Governance Programs
Topic 2: AI Operations	46%	- Incident Management and Resilience - Third-Party and Supply Chain Risk - AI System Lifecycle and Deployment - Operational Controls and Readiness - Performance Monitoring and Evaluation
Topic 3: AI Auditing Tools and Techniques	21%	- AI Audit Outputs and Reporting - Audit Evidence Collection Techniques - Audit Testing and Sampling Methodologies - Data Quality and Analytics for AI Audit - Audit Planning and Design

>> AAIA資格復習テキスト <<

更新するAAIA｜信頼的なAAIA資格復習テキスト試験｜試験の準備方法ISACA Advanced in AI Audit認定試験

AAIA試験に問題なく迅速に合格する方法答えは、有効で優れたAAIAトレーニングガイドにあります。既にAAIAトレーニング資料を用意しています。これらは、保証対象のプロのAAIA実践資料です。参考のために許容できる価格に加えて、3つのバージョンのすべてのAAIA試験資料は、10年以上にわたってこの分野の専門家によって編集されています。

ISACA Advanced in AI Audit 認定 AAIA 試験問題 (Q114-Q119):

質問 # 114
A retail organization uses an AI model to analyze customers' purchase history in order to offer personalized discounts. Which of the following practices represents the MOST ethical use of customer data?

A. Providing the public with access to review and audit the data set of collected customer information
B. Utilizing customer purchase data only after obtaining explicit consent and allowing customers to opt out
C. Sharing customer purchase data with third-party vendors to improve advertising and communication
D. Retaining and analyzing all available customer data to ensure unbiased recommendations

正解：B

解説：
The ethical use of customer data is rooted in respecting privacy, maintaining informed consent, and enabling data subjects to exercise control over their personal information. The AAIA™ Study Guide clearly outlines that obtaining explicit consent and providing opt-out capabilities align with principles of data protection and ethical AI.
"Ethical AI implementation includes transparency in data collection, clear consent mechanisms, and the right of users to opt out or control their personal data usage. Retail and consumer applications must ensure that personalized services do not override these data subject rights." Options B and D violate principles of minimal data use and consent, while C may create unnecessary privacy exposure. Therefore, A is the correct and most ethical practice.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Informed Consent and Customer Privacy"

質問 # 115
Which of the following is the MOST important course of action for an organization prior to allowing end users to utilize an AI tool?

A. Develop an AI policy with guidelines on appropriate use.
B. Implement baseline performance metrics.
C. Determine the impact to the disaster recovery plan (DRP).
D. Ensure a cybersecurity insurance clause is in place to include the use of AI.

正解：A

解説：
An AI usage policy sets the foundation for safe, ethical, and effective AI deployment. According to the AAIATM Study Guide, having an AI policy in place ensures that users understand acceptable behaviors, limitations, and responsibilities when interacting with AI tools.
"AI acceptable use policies promote governance by clearly outlining the dos and don'ts of AI interaction, preventing misuse and aligning user activity with organizational values and compliance standards."

質問 # 116
Which of the following AI documents would support an IS auditor assessing hyperparameter tuning records?

A. Explainability reports
B. Model development logs
C. Data sheets
D. Risk assessment reports

正解：B

解説：
Hyperparameter tuning involves adjusting settings like learning rate, batch size, or layer depth to optimize performance. This process is documented in " Model development logs, " which record the different " experiments " run by data scientists, the parameters used in each, and the resulting performance metrics (e.g., accuracy or loss). For an auditor, these logs are the " Audit Trail " of the model ' s construction. Data sheets (Option A) provide high-level info on datasets, and explainability reports (Option C) focus on outputs, but development logs provide the technical history of how the model was " tuned " to its final state.

質問 # 117
Which of the following is the BEST way to mitigate data poisoning in an AI model?

A. Rely on external third-party model providers.
B. Increase training data set size.
C. Use simpler algorithms to improve explainability.
D. Implement robust data validation protocols.

正解：D

解説：
Data poisoningoccurs when attackers manipulate training data to corrupt model behavior. The most direct mitigation is to implementrobust data validation and integrity checks(option C), including anomaly detection on input distributions, provenance controls, verification of data sources, and safeguards for pipelines feeding the training set. AAIA highlightsthreats and vulnerabilities specific to AIand the importance of controls that protect data integrity in AI Operations.
Option A (relying on third-party providers) does not inherently eliminate poisoning risk; providers themselves may be vulnerable. Option B (increasing data size) can dilute but not reliably remove malicious samples.
Option D (simpler algorithms) might help interpretability but does not directly prevent poisoned data from influencing the model. The most effective, aligned control isrigorous data validationto ensure only trustworthy data enters the training process.
References:
ISACA,AAIA Exam Content Outline- Domain 2: Threats and Vulnerabilities Specific to AI (controls for AI- related threats).
ISACA risk guidance referencing data integrity and poisoning risks in AI pipelines.

質問 # 118
An AI healthcare diagnostic tool requires large volumes of patient data, raising concerns about privacy and data breaches. Which of the following is the MOST effective strategy to mitigate this risk?

A. Limit the tool's access to only publicly available datasets.
B. Encrypt the data and transmit it through a secure channel.
C. Use synthetic data or anonymized data sets for model training.
D. Collect data from all patients to use for data analysis.

正解：C

解説：
The most effective strategy to protect sensitive patient data is to use synthetic data or anonymized datasets for model training. This reduces exposure of personally identifiable information while allowing the model to learn meaningful medical patterns.
AAIA emphasizes privacy-by-design, de-identification, and minimal use of raw personal data in high-risk sectors such as healthcare. Anonymization and synthetic data significantly reduce the risk of re-identification or breach-related harm.
Option A (encryption) protects data in transit but does not eliminate privacy risks. Option B is impractical because healthcare models require clinically relevant datasets, not public data. Option C increases data exposure, aggravating privacy risks.
Thus, using anonymized or synthetic data is the strongest privacy protection aligned with healthcare compliance principles.
References:
AAIA Domain 5: Data Privacy, AI Ethics, and Compliance.
AAIA Domain 2: Data Management Practices for Sensitive AI Use Cases.

質問 # 119
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