ISACA Advanced in AI Audit AAIA Dumps in PDF

Free ISACA AAIA Real Questions (page: 13)

Which of the following would pose the GREATEST risk when reviewing AI acceptable use training content?

  1. The content does not cover the use of effective prompting.
  2. The content does not cover the non-deterministic nature of AI.
  3. The content does not cover AI model architectures.
  4. The content does not cover required performance metrics.

Answer(s): B

Explanation:

Failing to address the non-deterministic nature of AI creates the greatest risk because users may incorrectly assume AI outputs are consistent, predictable, or authoritative. This misunderstanding can lead to overreliance on AI, improper validation of outputs, and significant governance and compliance issues.



An IS auditor is reviewing an AI application that uses customer data to refine the organization's marketing outreach strategies.
Which of the following should be the auditor's PRIMARY focus during this review?

  1. Alignment with organizational AI strategies
  2. Access control design and effectiveness
  3. Compliance with applicable privacy regulations
  4. Escalation protocols for sensitive data breaches

Answer(s): C

Explanation:

When customer data is used for AI-driven marketing, the primary risk is improper handling of personal data. Ensuring compliance with privacy regulations is essential to prevent unauthorized use, protect customer rights, and avoid legal or regulatory violations.



An organization is training a skin cancer recognition model. Photographs collected from which of the following sources would present the GREATEST risk associated with data integrity?

  1. Research facility receiving grants for cancer research
  2. Open-source data augmentation file
  3. Social media platform with images from all over the world
  4. Cohort of dermatologists with signed patient consent forms

Answer(s): C

Explanation:

Images from a social media platform pose the greatest data integrity risk because they lack verified clinical labeling, consistent image quality, and controlled collection conditions. This greatly increases the likelihood of incorrect or misleading training data for a medical diagnostic model.



An IS auditor examining change management procedures for an AI system observes inconsistent training data validation and verification protocols prior to model retraining.
Which of the following is the MOST significant risk in this context?

  1. Addition of AI model complexity due to inconsistent data inputs
  2. Noncompliance due to inadequate model training documentation
  3. Degradation of system reliability due to compromised or substandard data
  4. Delays in AI model retraining due to procedural inefficiencies

Answer(s): C

Explanation:

Inconsistent validation and verification of training data can allow corrupted, low-quality, or improperly prepared data into the retraining process, directly degrading the AI system’s reliability. This risk is more significant than documentation or timing issues because compromised data undermines the integrity and trustworthiness of the model’s outputs.



An AI healthcare diagnostic tool requires large volumes of patient data, raising concerns about privacy and data breaches.
Which of the following is the MOST effective strategy to mitigate this risk?

  1. Encrypt the data and transmit it through a secure channel.
  2. Limit the tool's access to only publicly available data sets.
  3. Collect data from all patients to use for data analysis.
  4. Use synthetic data or anonymized data sets for model training.

Answer(s): D

Explanation:

Using synthetic or anonymized data minimizes the exposure of identifiable patient information while still allowing the model to be trained effectively. This approach most effectively reduces privacy and breach risks compared to securing transmission or limiting data sources.



Which of the following is MOST important to consider when evaluating ethical risk related to data used for training an AI model?

  1. Ability to generate diverse outputs
  2. Sensitivity and origin of training data
  3. Frequency of model updates
  4. Cleaning and validation methods for training data

Answer(s): B

Explanation:

Ethical risk is primarily driven by the sensitivity and origin of training data, as these factors determine whether the data was collected appropriately, used with consent, and processed in a way that avoids harm, discrimination, or privacy violations.



Which of the following is the GREATEST concern when an audit team relies on generative AI to create audit reports?

  1. The reports may be more likely to reflect outdated information.
  2. The reports may contain misstatements resulting from hallucinations.
  3. The reports may use inconsistent formatting from prior audit findings.
  4. The reports may tend to use generic language for audit issues.

Answer(s): B

Explanation:

Generative AI can produce hallucinations — fabricated or incorrect statements — which can lead to inaccurate audit reports. This poses the greatest concern because it directly compromises the reliability and integrity of the audit’s conclusions.



Which of the following is the MOST important reason to conduct regular threat modeling exercises for AI systems and data?

  1. To proactively identify potential vulnerabilities in AI systems
  2. To assess the performance of AI algorithms
  3. To comply with AI regulatory requirements
  4. To prevent instances of AI model drift

Answer(s): A

Explanation:

Threat modeling enables proactive identification of vulnerabilities specific to AI systems and their data flows, allowing organizations to address security risks before they are exploited. This directly strengthens AI governance and risk management.



Share your comments for ISACA AAIA exam with other users:

B
Berihun
7/13/2023 7:29:00 AM

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nspk
1/19/2024 12:53:00 AM

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Muhammad Rawish Siddiqui
12/2/2023 5:28:00 AM

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Anonymous
7/14/2023 3:17:00 AM

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Mukesh
7/10/2023 4:14:00 PM

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12/11/2023 3:38:00 AM

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9/23/2023 8:37:00 AM

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9/10/2023 12:02:00 PM

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ethiopia
8/2/2023 2:18:00 AM

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whoAreWeReally
12/19/2023 8:29:00 PM

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9/2/2023 12:19:00 PM

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11/14/2023 11:02:00 AM

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11/21/2023 2:27:00 PM

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9/13/2023 5:27:00 PM

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5/24/2023 11:14:00 PM

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10/25/2023 10:48:00 PM

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10/18/2023 10:22:00 AM

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CW
7/11/2023 3:19:00 PM

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11/9/2023 8:53:00 AM

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11/4/2023 7:04:00 AM

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8/8/2023 9:40:00 PM

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CW
7/11/2023 2:51:00 PM

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10/23/2023 4:01:00 PM

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9/29/2023 8:19:00 AM

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7/29/2023 8:45:00 AM

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2/15/2023 11:04:00 PM

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Zaynik
9/17/2023 5:36:00 AM

questions and options are correct, but the answers are wrong sometimes. so please check twice or refer some other platform for the right answer

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Massam
6/11/2022 5:55:00 PM

90% of questions was there but i failed the exam, i marked the answers as per the guide but looks like they are not accurate , if not i would have passed the exam given that i saw about 45 of 50 questions from dump

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