Free AAISM Exam Braindumps
ISACA Advanced in AI Security Management Questions 141–145 (page: 30)

Updated On: 13-Sep-2026

AI developers often find it difficult to explain the processes inside deep learning systems PRIMARILY because:

  1. generated knowledge dynamically changes in memory without being tracked by change history logs.
  2. neural network architectures can include statistical methods that are not fully understood.
  3. applied algorithms are based on probability theories to improve system performance.
  4. training data input for learning is spread throughout the public domain and continues to change.

Answer(s): B

Explanation:

Deep learning systems rely on complex neural network architectures with many hidden layers and nonlinear interactions, making their internal decision processes difficult to interpret and explain, even though the underlying mathematics is known.



A preliminary risk assessment of a software as a service (SaaS)-based large language model (LLM) powered business support system has identified prompt injection, data poisoning, and model exfiltration as material threats.
Which of the following is the BEST approach to ensure risks are treated consistently?

  1. Applying control baselines from a recognized industry standard to AI components
  2. Implementing an AI threat control matrix that maps threats to specific controls and assurance activities
  3. Focusing resources on post-deployment red teaming and deferring control selection until post go-live feedback is received
  4. Relying on vendor independent audit reports and service level agreements (SLAs) as evidence of AI risk coverage

Answer(s): B

Explanation:

An AI threat control matrix ensures consistent risk treatment by explicitly mapping identified threats such as prompt injection, data poisoning, and model exfiltration to defined controls, ownership, and assurance activities across the AI system lifecycle.



Which of the following BEST describes the role of model cards in AI solutions?

  1. They are primarily used to visualize the performance of AI models.
  2. They provide a standardized way to document the training data and AI model use cases.
  3. They help developers create synthetic data and train AI models.
  4. They are used to automatically fine-tune AI models by adjusting hyperparameters based on user feedback.

Answer(s): B

Explanation:

Model cards provide a standardized way to document key information about an AI model, including its intended use, training data characteristics, limitations, ethical considerations, and performance context, supporting transparency, governance, and responsible use.



When evaluating a third-party AI service provider, which of the following master services agreement provisions is MOST critical for managing security risk?

  1. Guaranteeing unlimited model retraining requests
  2. Sharing real-time log information
  3. Prohibiting the use of customer data for model training
  4. Restricting query volume thresholds

Answer(s): C

Explanation:

Prohibiting the use of customer data for model training is most critical because it directly prevents unauthorized reuse, exposure, or persistence of sensitive data within the provider’s models, addressing one of the highest-impact security and privacy risks when using third-party AI services.



Which of the following is the PRIMARY purpose of a dedicated AI management system policy?

  1. Ensuring environmental impact is minimized
  2. Optimizing AI model accuracy
  3. Complying with external regulations
  4. Providing a framework to set AI objectives

Answer(s): D

Explanation:

A dedicated AI management system policy primarily provides a structured framework to define AI objectives, governance principles, roles, and accountability, ensuring AI initiatives are aligned with organizational strategy and managed consistently across their life cycle.



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