An organization concerned about the ethical and responsible use of a newly developed AI product should consider implementing:
Answer(s): A
Model cards provide transparent documentation of an AI model’s intended use, performance metrics, limitations, and ethical considerations. They help stakeholders understand how to use the model responsibly and ensure accountability in ethical AI deployment.
Which of the following metrics BEST evaluates the ability of a model to correctly identify all true positive instances?
Answer(s): D
Recall measures the proportion of actual positive instances that the model correctly identifies. It directly evaluates the model’s ability to capture all true positives, making it the most appropriate metric when completeness of detection is critical.
The PRIMARY reason to conduct a privacy impact assessment (PIA) on an AI system is to:
A privacy impact assessment (PIA) is conducted to systematically evaluate how personal data is collected, processed, stored, and shared by an AI system. This helps identify privacy risks, ensure compliance with data protection laws, and guide mitigation measures to protect individuals’ personal information.
Which of the following will BEST reduce data bias in machine learning (ML) algorithms?
Answer(s): C
Bias in ML algorithms often arises from unrepresentative or homogeneous training data. By diversifying the dataset - ensuring it includes a wide range of demographics, conditions, and scenarios - the model learns more balanced patterns, reducing systematic bias and improving fairness in predictions.
Which of the following should be done FIRST when developing an acceptable use policy for generative AI?
Before creating an acceptable use policy, the organization must clearly define what the AI will be used for and in which contexts. Establishing the scope and intended use provides a foundation for aligning the policy with regulatory requirements, legal considerations, and internal governance standards.
An organization needs large data sets to perform application testing. Which of the following would BEST fulfill this need?
AI data augmentation generates additional training or testing data by creating modified versions of existing datasets (e.g., through transformations, synthesis, or simulation). This approach expands dataset size while maintaining relevance and variability, supporting effective application testing without relying solely on external sources.
In the context of generative AI, which of the following would be the MOST likely goal of penetration testing during a red-teaming exercise?
Penetration testing in red-teaming aims to uncover vulnerabilities by crafting adversarial inputs that cause the model to produce unexpected, unsafe, or incorrect outputs - validating robustness and revealing exploitable failure modes.
Which of the following is MOST important for an organization to consider when implementing a preventive security safeguard into a new AI product?
Answer(s): B
Input sanitization ensures that any data fed into the AI system is clean, well-formed, and free from malicious content. As a preventive security safeguard, it reduces the risk of attacks (e.g., injection, poisoning, or adversarial inputs) before they can compromise the AI model’s behavior or integrity.
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