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>> Actual AAISM Test Answers <<
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NEW QUESTION # 100
Which of the following is MOST important to ensure security throughout the AI data life cycle?
Answer: B
Explanation:
AAISM emphasizes data lineage, provenance tracking, and inventory completeness as essential controls to ensure data security and accountability across all AI data life-cycle phases. This enables detection of unauthorized modifications, improper use, and compliance violations.
Periodic reviews (B) are necessary but insufficient without lineage. Restricting third-party use (C) is one control but not comprehensive. Open-source model choice (A) does not secure data.
References: AAISM Study Guide - AI Data Governance; Lineage and Traceability.
NEW QUESTION # 101
An organization recently introduced a generative AI chatbot that can interact with users and answer their queries. Which of the following would BEST mitigate hallucination risk identified by the risk team?
Answer: B
Explanation:
AAISM highlights fine-tuning foundational models as one of the most effective strategies for reducing hallucination risk. By tailoring the model with domain-specific, curated, and verified datasets, organizations can reduce the frequency of irrelevant or fabricated outputs. Testing and validation help evaluate risks but do not directly minimize hallucinations. Training on larger datasets may improve generalization but does not guarantee accuracy. Developer training in AI risk supports governance but is not a technical control against hallucinations. The best mitigation is fine-tuning to align the chatbot with trusted, context-specific knowledge.
References:
AAISM Study Guide - AI Risk Management (Hallucination and Output Integrity Risks) ISACA AI Security Management - Fine-tuning Generative Models
NEW QUESTION # 102
Cybersecurity teams should FIRST be embedded in the:
Answer: C
Explanation:
AAISM stresses that security must be embedded from the earliest phase--design, ensuring:
- threat modeling
- secure architecture
- data protection requirements
- system boundaries
- security-by-design principles
Introducing cybersecurity later increases unmitigated vulnerabilities.
NEW QUESTION # 103
Which of the following should be a PRIMARY consideration when defining recovery point objectives (RPOs) and recovery time objectives (RTOs) for generative AI solutions?
Answer: A
Explanation:
When setting RPOs and RTOs for AI systems, especiallygenerative AI, thecritical factor is the restoration of training data and model artifacts within the recovery window. Without this, restored systems may function inaccurately or incompletely, undermining business continuity.
AAISM risk management principles emphasize:
* Recovery objectives must align withdata protection requirementsfor both training and inference data.
* The ability to restorelarge-scale training datasetsis primary, since downtime without them leads to operational and compliance risks.
* Computational efficiency and hardware consistency are secondary considerations, but not the primary drivers of RPO/RTO definitions.
Thus, ensuring backup and restore capabilities of training datasets directly within RTO is theprimary requirement.
NEW QUESTION # 104
Which of the following is the BEST way to reduce the risk of misuse of an AI agent that has access to critical data and systems?
Answer: C
Explanation:
AAISM frameworks highlight output-based controls, including output filtering, restriction validation, and policy-aligned guardrails as primary defenses for AI agents with high privileges. Ensuring the agent does not output unauthorized instructions or sensitive data directly mitigates misuse.
Allowing user configuration (B) increases risk. Prohibiting manipulation entirely (C) is impractical. Reducing human oversight (D) increases system abuse potential.
References: AAISM Study Guide - AI Agents, Output Controls, and Guardrails.
NEW QUESTION # 105
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