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NO.90 Which of the following considerations should be prioritized when using an AI tool to select a sample for conducting an audit of a financial institution’s transaction processing system?

The transparency of the sampling process

The ability to process large volumes of data

The speed of sample generation

The historical performance in previous audits

NO.91 Which of the following is MOST important to have in place when initially populating data into a data frame for an AI model?

The box charts, histograms, scatterplots, and Venn diagrams that identify correlations and outliers

The code for separating data into training and testing data sets

An analysis of exploratory data that checks for incorrect data types, null values, and duplicate entries

An approved risk assessment for including, excluding, or subsequently dropping data attributes from the model

NO.92 The PRIMARY objective of machine learning (ML) in data processing is to:

Analyze data sets to identify visual patterns and trends.

Enhance the explainability of AI model outputs.

Perform actions that would typically require human intelligence.

Draw statistical inferences for creating artificial human intelligence.

NO.93 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?

Alignment with organizational AI strategies

Access control design and effectiveness

Compliance with applicable privacy regulations

Escalation protocols for sensitive data breaches

NO.94 Which of the following controls MOST effectively helps to ensure an AI model is resilient against external threats?

AI data set anonymization

Monitoring of AI model developers

Monitoring of AI access logs

AI model configuration testing

NO.95 When auditing the transparency of an AI system, which of the following would be the MOST effective way to understand the model’s decision-making process?

Evaluating the diversity of the training data set

Analyzing the complexity of the algorithms used

Assessing the computational cost of the model

Reviewing the explainability of AI outputs

NO.96 Which of the following is MOST important for an IS auditor to consider when collecting data for analysis by AI tools?

Data classification categories

Location of and access restrictions to the data

Data format and syntax requirements

Model weights used for AI training

NO.97 An organization deployed an AI-powered customer service chatbot trained using customer chat logs. During a risk assessment, which issue should be the IS auditor’s GREATEST concern?

Limited AI model capability to incorporate new data

Obsolete procedures leading to inadequate data integrity validation

Reputational impacts from inaccurate chatbot responses

Insufficient access controls leading to unauthorized customer data exposure

NO.98 When auditing a machine learning (ML) solution, false positives can BEST be assessed by examining the level of:

Precision

Completeness

Accuracy

Recall

NO.99 An AI tool is being implemented for a regional healthcare organization. Which of the following training methods BEST ensures the AI output does not reveal whether someone’s personal data was used?

Supervised learning with labeled patient records

Data augmentation during training to improve privacy

Differential privacy applied during model training

Transfer learning using public health data sets

NO.100 Which of the following would pose the GREATEST risk when reviewing AI acceptable use training content?

The content does not cover the use of effective prompting.

The content does not cover the non-deterministic nature of AI.

The content does not cover AI model architectures.

The content does not cover required performance metrics.

NO.101 Which of the following is the BEST reason that recurrent neural networks enable language translation of documents?

The process is sequential.

The process uses association rules.

The process is specialized for grid data.

The process is unidirectional.

NO.102 An IS auditor is testing an AI-based fraud detection system that flags suspicious transactions and finds that the system has a high false positive rate. Which of the following testing methods should be prioritized to BEST optimize the detection rate?

Regression testing

Cross-validation testing

Substantive testing

Benford’s Law analysis

NO.103 A healthcare organization uses an AI model to analyze patient data and provide diagnostic recommendations. Which of the following MOST effectively detects data drift related to the model’s predictions?

Comparing incoming patient data distributions with the training data set

Applying overrides to allow healthcare professionals to correct the AI model’s recommendations

Conducting periodic model retraining to ensure alignment with updated patient data

Using adversarial testing to simulate scenarios that stress test the model’s predictions

NO.104 Which of the following is the GREATEST risk of using AI to generate audit reports?

The AI system uses inconsistent formatting across audit reports.

The AI system misrepresents control effectiveness.

The AI system cannot integrate with management dashboard tools.

The AI system is not able to include historical audit findings.

NO.105 Which role is BEST suited to define the implementation roadmaps for adopting AI solutions?

Risk management committee

Steering committee

Product management

Internal audit

NO.106 Which of the following testing techniques would BEST validate whether an organization’s data governance program effectively ensures data quality and integrity for AI model training and deployment?

Performing a business impact analysis (BIA) to assess the consequences of AI model failure

Reviewing the organization’s AI software development life cycle documentation

Conducting a penetration test to identify vulnerabilities in the model

Assessing data lineage to verify the traceability of data sources

NO.107 A retail organization uses an AI model to forecast inventory based on customer purchasing trends and updates the model quarterly. The model recently failed to recognize a surge in demand during a popular shopping season. Which of the following issues does this situation BEST demonstrate?

Limited data set diversity impacting model training

Data drift impacting system forecasting

Overfitting issues due to a small training data set

Lack of outlier checks in data affecting forecast accuracy

NO.108 An organization is evaluating change management practices for AI-based decision support models. Which of the following BEST demonstrates effective AI-focused change management?

Engaging an independent expert to review the model’s accuracy and precision on a quarterly basis

Assigning a single data science team member to adjust the model in order to establish accountability

Documenting model updates and retraining sessions to ensure traceability

Deploying two separate copies of the model after each adjustment to compare results

NO.109 In the context of an AI implementation, which of the following actions is MOST critical for an organization’s change management program?

Ensuring the organization has a dedicated AI governance committee

Reviewing documentation for AI system changes, updates, and patches

Conducting a comprehensive risk assessment specific to AI-related changes

Verifying that all employees have completed mandatory AI ethics training

NO.110 The PRIMARY purpose of utilizing neural networks in AI is to:

Improve the user interface.

Increase computational power.

Mimic human decision making.

Minimize maintenance costs.

NO.111 Which of the following types of AI can use unlabeled data sets to imitate human learning behavior?

Supervised learning

Federated learning

Reinforcement learning

Unsupervised learning

NO.112 Which use case for an AI model to be used by a food delivery service would pose ethical risk to the organization?

Correlating time, cost, delivery distance, and customer satisfaction metrics to issue coupons to customers receiving substandard service

Basing driver retention and termination decisions on the number of delivered orders per total hours worked as compared to an industry benchmark

Comparing total food preparation and delivery time to an industry benchmark to set key performance and risk indicators for individual restaurants

Using customer service metrics for service speed and food quality to predict customer retention and forecast revenue

NO.113 An organization uses an AI-powered tool to detect and respond to cybersecurity threats in real time. An IS auditor finds that the tool produces excessive false positives, increasing the workload of the security team. Which of the following techniques should the auditor recommend to BEST evaluate the tool’s effectiveness in managing this issue?

Use a log analysis tool to examine the types and frequency of alerts generated.

Implement a benchmarking tool to compare the system’s alerting capability with industry standards.

Conduct penetration testing to assess the system’s ability to detect genuine threats.

Deploy a machine learning (ML) validation tool to increase the model’s accuracy and performance.

NO.114 Which of the following strategies used by modelers to enhance data accuracy has the GREATEST risk of bias and information loss?

Filling blank attributes in records with the mean, median, or mode within a grouping

Identifying and deleting duplicate entries in the data set

Separating multiple data attributes within one field into individual attribute columns

Placing numerical data into bins or buckets for a manageable quantity of correlations and result analyses

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