AAIR Practice Test 4 — 25 Questions

Question 1

Which governance mechanism is most effective for ensuring that AI ethical risks are addressed during the 'Design' phase of the AI Lifecycle?

Accepted Answer

Conducting a formal 'Ethics by Design' review as part of the AI project's stage-gate approval process.. Ethical AI reviews (sometimes called 'Ethics by Design' reviews) are proactive assessments conducted during the design phase to identify potential negative societal impacts before code is written, integrating ethics into the development lifecycle.

Answer

Scanning the source code for hardcoded credentials.

Answer

multi_select

Answer

Requiring a legal sign-off on the final model deployment.

Answer

multi_select

Answer

Reviewing the production logs for anomalies.

Question 2

When setting KPIs for an AI risk program, which metric is a leading indicator of potential model bias?

Accepted Answer

Demographic parity ratio in training data samples. Monitoring training data distribution is a leading indicator, whereas output monitoring is a lagging indicator.

Answer

Average model inference latency

Answer

Percentage of customer complaints regarding AI decisions

Answer

Number of model updates per quarter

Question 3

Which of the following is an example of an 'AI Risk Metric'?

Accepted Answer

Rate of false negatives in model output. The rate of false negatives in a credit approval model is a direct measure of AI-specific operational risk.

Answer

Budget spent on office supplies

Answer

Employee headcount in AI department

Answer

Number of coffee machines in the breakroom

Question 4

What is the key purpose of the 'Govern' function in the NIST AI RMF?

Accepted Answer

To establish the organizational culture, policy, and procedures for AI risk management.. The 'Govern' function focuses on the culture, policies, and structures that foster a risk-aware AI lifecycle.

Answer

To troubleshoot hardware issues.

Answer

To define the marketing strategy for the AI products.

Answer

To code the AI algorithms.

Question 5

Which documentation is necessary to provide to auditors for an AI system?

Accepted Answer

The model card or model documentation. A model card provides the necessary metadata, performance limitations, and intended use cases required for auditability.

Answer

A list of all employees who attended a conference

Answer

The login credentials for the production environment

Answer

The complete source code without comments

Question 6

Which TWO aspects of 'Data Governance' are critical for AI risk management?

Accepted Answer

Data access control and security. Data quality and security (access control) are the pillars of data governance for AI.

Answer

The number of pens in the supply closet

Answer

The speed of the local internet

Answer

The interior design of the office

Question 7

The board requires a new reporting structure for AI risk. Which TWO of the following should be included in the quarterly AI Risk Report to effectively communicate risk posture?

Accepted Answer

The status of the AI risk control roadmap and effectiveness of implemented mitigations.. Board reports need to focus on strategic risk alignment and the efficacy of the oversight process, specifically tracking the risk management pipeline and significant residual risks.

Answer

The raw output from the model's most recent training iteration.

Answer

The daily CPU and memory metrics for the inference clusters.

Answer

A list of all individual model parameters and weights.

Question 8

An enterprise is establishing an AI Governance Committee. Which organizational structure best ensures that risk management is integrated into the AI development lifecycle?

Accepted Answer

Cross-functional membership including Legal, Security, and Engineering. A cross-functional approach involving data science, legal, compliance, and IT security ensures risk is addressed at every SDLC phase.

Answer

Centralized control under the Chief Data Officer

Answer

External advisory board oversight

Answer

Automated AI risk assessment tools alone

Question 9

Which THREE factors should be evaluated when reviewing an AI model for 'Fairness'?

Accepted Answer

Performance disparity across different demographic cohorts.. Fairness assessment covers data representation, metric definitions, and outcome disparities.

Answer

The number of hours the server was powered on.

Answer

The model's file size in kilobytes.

Question 10

Which TWO items are considered 'AI Model Artifacts' that should be kept for audit purposes?

Accepted Answer

The training dataset version. Documentation and training parameters are crucial for reproducing and auditing model behavior.

Answer

The lunch menu for the developers

Answer

The name of the company's favorite mascot

Answer

The local weather report from last week

Question 11

Which THREE roles should have oversight authority in the AI Risk Program?

Accepted Answer

Chief Technology Officer. Oversight requires representatives from business, technology, and risk management.

Answer

The company's social media influencer

Answer

The office receptionist

Question 12

A firm is using the NIST AI Risk Management Framework to document its AI risk program. Which approach best ensures that AI risk metrics are dynamic?

Accepted Answer

Integrating model performance metrics into operational dashboards. Mapping specific risk indicators to model performance monitoring allows metrics to evolve as the model's environment changes.

Answer

Conducting annual risk assessments

Answer

Setting static thresholds for model accuracy

Answer

Limiting AI deployment to offline systems

Question 13

Which role is primarily responsible for ensuring that AI-generated content adheres to intellectual property risk policies?

Accepted Answer

Chief Legal Officer. The Chief Legal Officer or Legal counsel is accountable for IP rights and contractual obligations related to AI output.

Answer

System Administrator

Answer

Product Manager

Answer

Data Engineer

Question 14

Which phase of the AI lifecycle is most critical for initial risk mitigation?

Accepted Answer

Design and Problem Formulation.. Risk mitigation is most effective during the Design phase, before the model is developed, to avoid costly re-engineering.

Answer

Deployment.

Answer

Decommissioning.

Answer

Model Monitoring.

Question 15

You are auditing an AI project. Which finding suggests a failure in AI risk management governance?

Accepted Answer

No individual is designated as the accountable owner for the model's production outcomes.. If no one is designated as accountable for the model's outcomes, the governance structure is non-existent or dysfunctional.

Answer

The model was trained on historical data.

Answer

The team uses a cloud-based GPU provider.

Answer

The model has a 2% prediction error rate.

Question 16

The organization is updating its 'AI Risk Management Policy'. Which THREE components are essential to ensure it aligns with the 'Manage' function of the NIST AI RMF?

Accepted Answer

A defined mechanism for reporting and remediating non-compliant AI systems.. The 'Manage' function involves implementing controls. Essential components include clear policies on prioritization, documented operational procedures, and a process for ongoing monitoring and improvement.

Answer

The marketing budget for upcoming AI product launches.

Answer

A list of all employees who have access to the source code repository.

Question 17

When drafting an AI risk policy, which element must be defined to provide clear guidance on acceptable AI outcomes?

Accepted Answer

Risk appetite statement. Risk appetite statements provide the boundary of acceptable risk, which is foundational to any AI risk management program.

Answer

AI model training data source list

Answer

Vendor procurement list

Answer

Technical architecture diagram

Question 18

A company is scaling its AI initiatives across five business units. What is the most effective way to ensure consistent risk measurement?

Accepted Answer

Implementing a centralized AI risk taxonomy. Standardizing a taxonomy ensures that all business units report risks using the same language and impact levels.

Answer

Using different platforms for each business unit

Answer

Allowing each business unit to define its own risk metrics

Answer

Focusing only on the highest-risk model

Question 19

An organization is establishing an AI governance framework. Which approach is most effective for aligning AI risk appetite with enterprise-wide risk management (ERM)?

Accepted Answer

Map AI-specific risk metrics to existing enterprise risk categories like operational, financial, and reputational risk.. Integrating AI risk appetite into the existing ERM framework ensures consistency and avoids silos.

Answer

Establish a top-down mandate that ignores business unit input to ensure uniformity.

Answer

Focus solely on technical model performance metrics to define the organizational risk appetite.

Answer

Create a separate AI-specific risk register that operates independently of the corporate risk register.

Question 20

When an AI model fails in production, what is the 'Post-Mortem' goal?

Accepted Answer

To identify root causes and update risk management practices. The goal is to identify the root cause so that the AI risk framework can be updated to prevent recurrence.

Answer

To hide the failure from management

Answer

To fire the developer responsible

Answer

To delete all logs associated with the model