Which data preparation method simplifies data correlations but presents the GREATEST risk for introducing bias?
Answer(s): A
Using the mode of a column to fill missing values simplifies correlations but presents the greatest risk of introducing bias. It disproportionately reinforces the majority value, distorting data distribution and reducing fairness in model training.
Which of the following controls would BEST minimize the risk of bias introduced into AI models from flawed training data?
Answer(s): D
Performing cross-validation of AI models best minimizes the risk of bias from flawed training data. Cross-validation evaluates model performance across multiple subsets of data, helping to detect and reduce overfitting or biased patterns before deployment.
When auditing an AI model's change management process, which of the following is MOST crucial to ensure the model’s integrity and compliance?
Answer(s): C
Monitoring the AI model’s predictions using different data to detect anomalies is most crucial in change management. It ensures the integrity of the model after updates and validates compliance by detecting unintended deviations or risks.
A logistics company uses an AI model to optimize delivery routes. Which of the following methods would BEST verify the model’s accuracy?
An IS auditor observes that an organization is using generative AI to analyze a large data set. The generative AI has a context limitation of 8,000 tokens, while the data set contains 1,000,000 rows. Which of the following is the MOST significant risk in this situation?
The most significant risk is that the AI will analyze only a portion of the data set due to the context limitation. This leads to incomplete analysis and potentially inaccurate or biased conclusions.
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