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질문 # 332
When addressing privacy concerns related to AI systems, which of the following is the GREATEST significance of user consent for an organization?
정답：B
설명：
Within AAISM's privacy governance, consent is a lawful basis that authorizes processing of personal data for defined purposes. Its principal significance is granting the organization the authority to process user data in AI workflows in line with stated purposes and limits. While fairness (A) and security controls (C) are essential, they are distinct obligations; data subject rights such as rectification/erasure (B) exist regardless of consent and are not "enabled" by it. Therefore, the greatest significance of consent is that it legally permits processing under declared purposes and constraints.
References: AI Security Management™ (AAISM) Body of Knowledge - Privacy & Data Protection in AI; Lawful Basis and Purpose Limitation. AAISM Study Guide - Consent, Transparency, and Data Subject Rights; Privacy-by-Design Controls in AI Pipelines.
질문 # 333
Which of the following approaches BEST helps to reduce model bias?
정답：D
설명：
AAISM frames bias risk primarily as a data problem. The most impactful mitigation is to ensure diversity and representativeness of training data sources, thereby reducing sampling bias and improving fairness across subpopulations. More labels per instance (A) does not correct coverage gaps; reducing update cadence (B) can entrench existing bias; and higher model complexity (C) may overfit or obscure bias without addressing root causes. Diverse, representative datasets-paired with fairness testing-are the recommended first-line control.
References: AI Security Management™ (AAISM) Body of Knowledge - Bias Identification and Mitigation; Data Quality and Representativeness. AAISM Study Guide - Fairness Risk Controls; Dataset Curation and Coverage Analysis.
질문 # 334
The PRIMARY reason to conduct a privacy impact assessment (PIA) on an AI system is to:
정답：A
설명：
According to AAISM privacy governance guidance, the primary reason for conducting a PIA is to analyze how personal data is collected, processed, shared, and retained by an AI system. This analysis ensures compliance with privacy laws, mitigates risks to individuals, and informs necessary safeguards. Identifying regulations is part of compliance but is secondary to analyzing actual data handling. Building customer confidence is an outcome, not the main purpose. Checking for poisoned data relates to data quality, not privacy assessment. The fundamental purpose of a PIA is therefore to analyze the handling of personal data.
References:
AAISM Study Guide - AI Governance and Program Management (Privacy Impact Assessments) ISACA AI Security Management - Data Handling and Privacy Risk
질문 # 335
Which of the following information is MOST important to include in a centralized AI inventory?
정답：B
설명：
AAISM governance practices identify ownership and accountability as the most critical element in any centralized AI inventory. An AI inventory provides oversight by cataloging all AI assets within an organization, and assigning responsibility ensures that each system has clear governance, monitoring, and compliance coverage. While use cases, training data, and registries are valuable metadata, they do not guarantee accountability. Without defined ownership, no party is responsible for addressing risk, bias, or incidents. Therefore, the most important information to include is ownership and accountability details for each AI system.
질문 # 336
When evaluating a third-party AI service provider, which master services agreement (MSA) provision is MOST critical for managing security risk?
정답：B
설명：
AAISM emphasizes strong contractual restrictions on how vendors use customer data, especially prohibiting vendors from using customer inputs to train or fine-tune shared models.
This protects against:
* data leakage
* intellectual property exposure
* regulatory violations
* shadow training of external models
Log sharing (B) and query limits (D) are operational controls but do not directly prevent data misuse.
Unlimited retraining (A) has no relevance to security.
References: AAISM Study Guide - Vendor Risk Management; Data Usage Restrictions in Contracts.
질문 # 337
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