A data science team has developed a machine learning model for credit scoring. The risk team needs to assess the model's performance across different demographic groups to identify potential bias before deployment. Which tool is most appropriate for this task?

Model validation tools that include fairness metrics

Monitoring systems for drift detection

Data loss prevention (DLP) tools

Which of the following is a primary purpose of the NIST AI Risk Management Framework (AI RMF)?

To provide a structured approach for organizations to manage risks related to AI systems throughout their lifecycle.

To mandate specific technical controls that all AI systems must implement to be compliant.

To certify AI systems as safe and trustworthy for public use.

To replace the NIST Cybersecurity Framework for all technology risk management.

A financial services company is deploying an AI system for loan approvals. The compliance team must ensure the AI risk management approach aligns with the organization's existing enterprise risk management and cybersecurity processes. Which framework would best provide a structured, internationally recognized approach specifically for AI risk management that can be integrated with the broader risk management system?

NIST Cybersecurity Framework (CSF) 2.0

OWASP Top 10 for LLM Applications

A company is using the NIST Cybersecurity Framework (CSF) to manage cybersecurity risks. They are now adopting an AI system and want to ensure AI risks are managed consistently. Which action best integrates AI risk management into the existing CSF-based process?

Add AI-specific risk categories to the existing risk register and map them to CSF functions

Use only the NIST AI RMF and stop using the CSF

Create a separate risk register for AI risks

Ignore AI risks until they materialize

What is a key benefit of integrating AI risk management with broader cybersecurity risk management processes?

It enables a unified and consistent approach to managing risks across AI and traditional IT systems.

It guarantees that all AI risks are automatically mitigated.

It ensures that AI systems are exempt from cybersecurity controls.

It eliminates the need for separate risk assessments for AI systems.

Dell NIST Cybersecurity Framework v2.0

Domain 10Objective 6

Describe AI Risk Management Frameworks, Tools, and Techniques. NIST-CYBERSECURITY-FRAMEWORK-2 Practice Questions (Page 2)

Part of the Assess Cybersecurity Risk Communication and Integration domain, which accounts for 10% of the NIST-CYBERSECURITY-FRAMEWORK-2 exam.

21questions here

5free pages

4concepts

10%of the exam

Questions 6–10

6application · medium
A data science team has developed a machine learning model for credit scoring. The risk team needs to assess the model's performance across different demographic groups to identify potential bias before deployment. Which tool is most appropriate for this task?
Select an answer first
7foundation · easy
Which of the following is a primary purpose of the NIST AI Risk Management Framework (AI RMF)?
Select an answer first
8application · medium
A financial services company is deploying an AI system for loan approvals. The compliance team must ensure the AI risk management approach aligns with the organization's existing enterprise risk management and cybersecurity processes. Which framework would best provide a structured, internationally recognized approach specifically for AI risk management that can be integrated with the broader risk management system?
Select an answer first
9application · medium
A company is using the NIST Cybersecurity Framework (CSF) to manage cybersecurity risks. They are now adopting an AI system and want to ensure AI risks are managed consistently. Which action best integrates AI risk management into the existing CSF-based process?
Select an answer first
10foundation · easy
What is a key benefit of integrating AI risk management with broader cybersecurity risk management processes?
Select an answer first

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