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NEW QUESTION # 145
Which of the following is the GREATEST risk of using AI to generate audit reports?
Answer: B
Explanation:
The greatest risk when using AI to generate audit reports is that it may misrepresent control effectiveness (B)--for example, by overstating the robustness of controls, understating deficiencies, or summarizing findings inaccurately. This undermines the reliability of the entire audit and can lead to poor management decisions, regulatory issues, and reputational damage.
AAIA emphasizes that AI-generated artifacts still require professional judgment and validation to ensure they accurately reflect audit evidence and conclusions.
NEW QUESTION # 146
Which of the following is the BEST way to ensure an AI model ' s outputs are effectively controlled for bias?
Answer: C
Explanation:
The most objective evidence of bias control is " Performance Parity " . If the accuracy, precision, and recall are " Similar across various demographic groups, " it demonstrates that the model is functioning equitably for all users. While having a policy definition (Option B) is good governance, it doesn ' t prove the model is fair in practice. Restricting training to " Real-world human decisions " (Option C) often introduces bias, as it simply automates historical human discrimination. Transparency (Option D) is necessary for auditing but does not, on its own, prevent a model from being biased.
NEW QUESTION # 147
Which of the following techniques BEST supports machine learning (ML) training in sentiment analysis?
Answer: C
Explanation:
Sentiment analysis is a classification task where text is categorized (e.g., positive, negative, or neutral).
Logistic regression is a fundamental and highly effective statistical method for binary or multi-class classification, making it a standard choice for sentiment models. It estimates the probability of an input belonging to a specific class. While more complex architectures like Transformers (LLMs) are now common, logistic regression remains a benchmark for its simplicity and transparency in audit contexts. Image recognition and ANOVA are not relevant to the linguistic processing required for sentiment analysis, and the log-rank test is typically used in survival analysis rather than NLP classification.
NEW QUESTION # 148
An organization deploys an AI recruitment platform to screen job applicants. The IS auditor identifies that the platform's decisions may be influenced by model bias. Which of the following risk mitigation strategies is BEST for the auditor to recommend?
Answer: C
Explanation:
Periodic testing and monitoring for bias is a sustainable, proactive strategy aligned with best practices outlined in the AAIATM Study Guide. This approach ensures that the AI system remains compliant over time, even as data and hiring conditions change.
"Ongoing fairness assessments help detect emerging biases and ensure that the AI model maintains equitable decision-making standards. Periodic testing also allows organizations to take corrective action before regulatory or reputational damage occurs."
NEW QUESTION # 149
A bank is deploying an AI model trained on customer transactions in a multi-cloud environment.
Which of the following BEST supports regulatory compliance regarding data security and privacy?
Answer: B
Explanation:
In a multi-cloud environment, data often traverses various geographical regions. For financial institutions, "Data residency and sovereignty" are the most critical compliance factors, ensuring that data is stored and processed within the jurisdictions required by law (e.g., GDPR or local banking acts). Failure to control where data resides can lead to severe legal penalties. While
"Privacy by Design" and "DPIA" are essential methodologies, they do not specifically address the physical and legal location of data across cloud providers. Sovereignty controls ensure the bank maintains control over its data assets and complies with specific cross-border data transfer regulations.
NEW QUESTION # 150
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