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[General] AAIA合格問題 & AAIA模擬試験サンプル

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【General】 AAIA合格問題 & AAIA模擬試験サンプル

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短い時間に最も小さな努力で一番効果的にISACAのAAIA試験の準備をしたいのなら、Xhs1991のISACAのAAIA試験トレーニング資料を利用することができます。Xhs1991のトレーニング資料は実践の検証に合格すたもので、多くの受験生に証明された１００パーセントの成功率を持っている資料です。Xhs1991を利用したら、あなたは自分の目標を達成することができ、最良の結果を得ます。
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.

AAIA試験の準備方法｜実際的なAAIA合格問題試験｜素敵なISACA Advanced in AI Audit模擬試験サンプルXhs1991はISACAのAAIA「ISACA Advanced in AI Audit」試験に向けて問題集を提供する専門できなサイトで、君の専門知識を向上させるだけでなく、一回に試験に合格するのを目標にして、君がいい仕事がさがせるのを一生懸命頑張ったウェブサイトでございます。
ISACA Advanced in AI Audit 認定 AAIA 試験問題 (Q14-Q19):質問 # 14
Which of the following is MOST important to review in order to gain assurance that an AI model is performing without biases?
  • A. AI training data
  • B. AI development environment
  • C. AI model temperature
  • D. AI model adaptability
正解：A

質問 # 15
Which of the following is an IS auditor MOST likely to use in order to ensure an AI model has the ability to make correct predictions?
  • A. Confusion matrix
  • B. Adversarial testing
  • C. Latency testing
  • D. Group analysis
正解：A
解説：
The confusion matrix is a key performance evaluation tool in machine learning and AI auditing. According to the AAIA™ Study Guide, a confusion matrix presents detailed information about actual versus predicted classifications, allowing auditors to assess accuracy, precision, recall, and F1 scores.
"A confusion matrix reveals not just how often predictions are correct, but also the types of errors being made-false positives and false negatives-thereby providing a clear view of the model's predictive reliability." Adversarial testing evaluates robustness, group analysis identifies bias across subgroups, and latency testing examines performance speed-not predictive accuracy. Thus, D is the most relevant for ensuring correct predictions.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Operations and Performance," Subsection: "Model Evaluation Metrics"

質問 # 16
From a data appropriateness and bias perspective, which of the following should be of GREATEST concern when reviewing an AI model used in a credit scoring system?
  • A. The model incorporates the applicant's loan history to assess spending habits.
  • B. The model utilizes historical credit data to predict future credit behavior.
  • C. The model uses postal codes as a primary factor in determining creditworthiness.
  • D. The model considers the applicant's income level as a key factor in the credit decision.
正解：C

質問 # 17
When an IS auditor is reviewing results from an AI system, which of the following would cause the GREATEST risk?
  • A. Inability to identify where an AI system is housed
  • B. System output not being checked for inconsistencies
  • C. Difficulty of documenting AI algorithm processes
  • D. Cascading failures of AI system outputs
正解：B
解説：
Unchecked AI outputs pose a significant risk because incorrect or biased results may propagate into decision- making processes. The AAIA™ Study Guide stresses that validating AI outputs for consistency, accuracy, and reasonableness is a critical responsibility of both operators and auditors.
"Auditors must verify that appropriate output validation mechanisms are in place. Failure to check outputs increases the likelihood of undetected errors influencing downstream processes or decisions." While cascading failures (C) are a consequence of unchecked outputs, B is the root issue. A and D present logistical and documentation risks but not the highest immediate impact.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI in Audit Processes," Subsection: "Audit Validation of AI Outputs"

質問 # 18
A healthcare organization uses data clustering to group patients by medical history for personalized treatment recommendations. Which of the following is the GREATEST privacy risk associated with this practice?
  • A. Clusters can reveal sensitive personal information depending on how the information is presented.
  • B. The clustering requires more data, increasing the risk of a privacy breach.
  • C. Clustering increases the complexity of the model, making data harder to anonymize.
  • D. Irrelevant features in the data may result in inaccurate or biased treatments.
正解：A
解説：
Clustering, especially in sensitive domains like healthcare, can inadvertently expose confidential patient data if the resulting groups are too specific or reveal underlying health conditions. The AAIA™ Study Guide warns that clustering can increase privacy risks when small, homogenous groups are formed that effectively re-identify individuals or reveal sensitive traits.
"Clustering results must be carefully reviewed to prevent indirect re-identification or unintended exposure of sensitive traits. Ethical handling of aggregated patient data is essential to protect individual privacy." While A and B involve general concerns, and C focuses on performance, D directly addresses the most significant privacy threat: exposure through cluster outputs.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Data Anonymization and Re-identification Risks"

質問 # 19
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ISACA AAIA認定資格試験の難しさなので、我々サイトAAIAであなたに適当する認定資格試験問題集を見つけるし、本当の試験での試験問題の難しさを克服することができます。当社はISACA AAIA認定試験の最新要求にいつもでも関心を寄せて、最新かつ質高い模擬試験問題集を準備します。また、購入する前に、無料のPDF版デモをダウンロードして信頼性を確認することができます。
AAIA模擬試験サンプル: https://www.xhs1991.com/AAIA.html
https://www.fast2test.com
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