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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q39-Q44):

NEW QUESTION # 39
An organization using an AI model for financial forecasting identifies inaccuracies caused by missing data.
Which of the following is the MOST effective data cleaning technique to improve model performance?

• A. Increasing the frequency of model retraining with the existing data set
• B. Deleting outlier data points to prevent unusual values impacting the model
• C. Tuning model hyperparameters to increase performance and accuracy
• D. Applying statistical methods to address missing data and reduce bias

Answer: D

Explanation:
The AAISM study content emphasizes that data quality management is a central pillar of AI risk reduction.
Missing data introduces bias and undermines predictive accuracy if not addressed systematically. The most effective remediation is to apply statistical imputation and related methods to fill in or adjust for missing values in a way that minimizes bias and preserves data integrity. Retraining on flawed data does not solve the underlying issue. Deleting outliers may harm model robustness, and hyperparameter tuning optimizes model mechanics but cannot resolve missing information. Therefore, the proper corrective technique for missing data is the application of statistical methods to reduce bias.
References:
AAISM Study Guide - AI Risk Management (Data Integrity and Quality Controls) ISACA AI Governance Guidance - Data Preparation and Bias Mitigation

 

NEW QUESTION # 40
Which of the following would MOST effectively ensure an organization developing AI systems has comprehensive data classification and inventory management?

• A. Conducting quarterly audits of AI data sets for anomalies and missing metadata
• B. Creating a centralized team to oversee the classification of data used in AI projects
• C. Implementing an automated data cataloging tool that integrates with all organizational data repositories
• D. Establishing a manual process to categorize data based on business needs and regulatory compliance

Answer: C

Explanation:
AAISM governance practices emphasize automation as the most effective way to maintain comprehensive, accurate, and scalable data classification and inventory management. An automated data cataloging tool integrated with all repositories ensures continuous visibility, reduces human error, and supports regulatory compliance. Centralized teams and manual processes provide oversight but cannot achieve the same scale and consistency. Periodic audits detect issues but are reactive rather than proactive. For effective governance, the best solution is automated cataloging integrated across data repositories.
References:
AAISM Study Guide - AI Governance and Program Management (Data Classification and Inventory) ISACA AI Security Management - Automated Data Cataloging for AI Projects

 

NEW QUESTION # 41
To ensure AI tools do not jeopardize ethical principles, it is MOST important to validate that:

• A. Outputs of AI tools do not perpetuate adverse biases
• B. Stakeholders have approved alignment with company values
• C. AI tools are evaluated by the privacy department before implementation
• D. The organization has implemented a responsible development policy

Answer: A

Explanation:
AAISM highlights that the core ethical risk in AI is the perpetuation of bias that results in unfair or discriminatory outcomes. Therefore, the most important validation step is ensuring that outputs of AI systems are free from adverse biases. A responsible development policy, stakeholder approvals, and privacy reviews all contribute to governance, but they do not directly ensure ethical outcomes. Validation of output fairness is the critical safeguard for ensuring AI does not violate ethical principles.
References:
AAISM Study Guide - AI Risk Management (Bias and Ethics Validation)
ISACA AI Security Management - Ethical AI Practices

 

NEW QUESTION # 42
An organization is facing a deepfake attack intended to manipulate stock prices. The organization's crisis communication plan has been activated. Which of the following is MOST important to include in the initial response?

• A. Conduct employee awareness training on recognizing deepfake videos and audio
• B. Provide clarifying information in a pre-approved public statement
• C. Conduct a detailed forensic analysis to identify the source of the deepfake
• D. Engage with brand monitoring services to track social media activity

Answer: B

Explanation:
AAISM guidance on crisis management and communication emphasizes that the initial priority in responding to a reputational or market manipulation attack is to provide accurate clarifying information to the public through a pre-approved statement. This ensures stakeholders and markets are given verified facts immediately, limiting the spread of misinformation. While forensic analysis, employee training, and monitoring activities are important, they occur after the immediate need for public trust and damage control is addressed. Pre-approved statements are a central control in AI-related incident response to ensure consistency, timeliness, and credibility in communications.
References:
AAISM Study Guide - AI Governance and Program Management (Incident Response and Crisis Communication) ISACA AI Security Management - Public Communication and Trust Preservation

 

NEW QUESTION # 43
Which of the following is MOST important to consider when validating a third-party AI tool?

• A. Terms and conditions
• B. Industry analysis and certifications
• C. Right to audit
• D. Roundtable testing

Answer: C

Explanation:
The AAISM framework specifies that when adopting third-party AI tools, the right to audit is the most critical contractual and governance safeguard. This ensures that the organization can independently verify compliance with security, privacy, and ethical requirements throughout the lifecycle of the tool. Terms and conditions provide general usage guidance but often limit liability rather than ensuring transparency. Industry certifications may indicate good practice but do not substitute for direct verification. Roundtable testing is useful for evaluation but lacks enforceability. Only the contractual right to audit provides formal assurance that the tool operates in accordance with organizational policies and external regulations.
References:
AAISM Exam Content Outline - AI Governance and Program Management (Third-Party Governance) AI Security Management Study Guide - Vendor Oversight and Audit Rights

 

NEW QUESTION # 44
......

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