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NEW QUESTION # 70
An organization plans to use AI to analyze the shopping patterns of its customers to predict interests and send targeted, customized marketing emails. Which of the following should be done FIRST?
Answer: D
Explanation:
The first action, before any processing of personal data for AI-driven profiling and targeted communications, is to establish a lawful basis for processing. Under AAISM-aligned privacy governance, explicit and informed consent is prioritized for new or sensitive uses such as interest profiling and targeted marketing.
Consent ensures purpose limitation, transparency, and user control prior to model ingestion and campaign activation. Training teams, updating terms of service, or verifying contact details are important, but they do not provide legal authority to process data; therefore, they follow after consent is obtained.
References: AI Security Management (AAISM) Body of Knowledge - Privacy Governance and Lawful Basis; Purpose Limitation and Transparency; Consent Management in AI-enabled Marketing. AAISM Study Guide - Data Protection Controls for AI Profiling; Consent Capture and Record-Keeping.
NEW QUESTION # 71
Which of the following BEST strengthens information security controls around the use of generative AI applications?
Answer: A
Explanation:
AAISM identifies continuous monitoring of AI outputs-especially generative outputs-as the most effective security control, ensuring that violations, unsafe responses, data leakage, and policy-breaking behavior are detected and corrected.
A kill switch (C) is a last-resort measure, not a primary control. Exceeding benchmarks (A) does not ensure relevance. Validating training data (D) is important but insufficient for generative output risks.
References: AAISM Study Guide - Generative AI Security Controls; Output Monitoring and Policy Alignment.
NEW QUESTION # 72
The PRIMARY purpose of adopting and implementing AI architecture as part of an organizational AI program is to:
Answer: B
Explanation:
An AI architecture, within program governance, exists to align AI system components and lifecycle processes with business goals and policy constraints. Architecture provides the organizing structure linking strategy, capabilities, processes, data, models, controls, and assurance so that AI outcomes are traceable to business value, risk appetite, and compliance expectations. Efficiency, speed, and threat analysis are important architectural qualities, but they are not the primary purpose; the primary purpose is strategic and governance alignment so that technical choices and controls consistently realize organizational objectives.
NEW QUESTION # 73
A health services organization is developing a proprietary generative AI chatbot to assist patients with medical devices. Which of the following should be the organization's HIGHEST priority?
Answer: A
Explanation:
AAISM prioritizes training data suitability-lawful sourcing, provenance, quality, representativeness, and safety-especially in health-related applications. The correctness and appropriateness of training data determine clinical safety, reduction of harmful outputs, and compliance with data protection/sector obligations. Larger models or more data do not compensate for inappropriate or low-quality datasets; tuning is secondary to ensuring the right data with rigorous curation, labeling quality, and guardrails aligned to patient safety requirements.
References:* AI Security Management (AAISM) Body of Knowledge: Data Governance & Quality; High- Risk/Health Context Controls; Safety & Harm Minimization* AAISM Study Guide: Data Provenance & Suitability, Domain-Specific Dataset Controls; Compliance-by-Design for Sensitive Sectors
NEW QUESTION # 74
An attacker crafts inputs to a large language model (LLM) to exploit output integrity controls. Which of the following types of attacks is this an example of?
Answer: A
Explanation:
According to the AAISM framework, prompt injection is the act of deliberately crafting malicious or manipulative inputs to override, bypass, or exploit the model's intended controls. In this case, the attacker is targeting the integrity of the model's outputs by exploiting weaknesses in how it interprets and processes prompts. Jailbreaking is a subtype of prompt injection specifically designed to override safety restrictions, while evasion attacks target classification boundaries in other ML contexts, and remote code execution refers to system-level exploitation outside of the AI inference context. The most accurate classification of this attack is prompt injection.
References:
AAISM Exam Content Outline - AI Technologies and Controls (Prompt Security and Input Manipulation) AI Security Management Study Guide - Threats to Output Integrity
NEW QUESTION # 75
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