AAIA Practice Test 10 — 10 Questions

Question 1

Which TWO are common 'AI Operational' challenges?

Accepted Answer

Data quality management. Managing data quality and model maintenance are core challenges.

Answer

Selecting a font

Answer

Writing poetry

Answer

Buying new office chairs

Question 2

Which THREE risks should be explicitly managed in an 'AI Governance' program?

Accepted Answer

Operational performance degradation. Governance must manage bias, security, and performance risks.

Answer

The choice of font for the final report

Answer

The color of the server room lights

Question 3

In Azure Machine Learning, which component should an auditor verify to ensure model registry access is restricted to authorized CI/CD service principals?

Accepted Answer

Workspace Access Control (IAM). Access to the Model Registry is governed by Azure RBAC and specifically Managed Identities/Service Principals assigned to the workspace.

Answer

Environment YAML files

Answer

Compute Instance logs

Answer

Data labeling projects

Question 4

In the context of 'AI Pipelines', what is the role of a 'Model Registry'?

Accepted Answer

Version control for model artifacts. The Model Registry provides a central repository to store, version, and manage the lifecycle of trained models.

Answer

Storing training logs

Answer

Monitoring compute costs

Answer

Optimizing SQL queries

Question 5

An organization uses AWS SageMaker. As an auditor, you need to verify that model lineage and versioning are being captured to satisfy the AI risk assessment requirement for reproducibility. Which feature ensures that every model training job is recorded with its data sources?

Accepted Answer

SageMaker Lineage Tracking. SageMaker Lineage Tracking automatically captures the relationship between data, models, and training jobs to ensure full auditability.

Answer

AWS CloudTrail

Answer

SageMaker Clarify

Answer

SageMaker Model Registry

Question 6

In the context of AI Operations, what does 'CI/CD' stand for?

Accepted Answer

Continuous Integration and Continuous Deployment. Continuous Integration and Continuous Deployment/Delivery.

Answer

Computer Intelligence and Cloud Data

Answer

Continuous Inference and Cloud Deployment

Answer

Code Integration and Cloud Delivery

Question 7

Which TWO of the following are examples of 'Model Risk Management' (MRM) controls that must be validated during an audit?

Accepted Answer

Post-deployment performance and drift monitoring. Model validation and ongoing performance monitoring are the standard controls used to manage model risk after deployment.

Answer

Automated deployment pipeline triggers

Answer

Standardized IDE choice for developers

Answer

Increasing training dataset size by 50%

Question 8

In a CI/CD pipeline for AI, where should the 'Model Validation' gate be located?

Accepted Answer

Between training and registration. Validation must occur after training but before model registration to prevent bad models from reaching production.

Answer

During feature engineering

Answer

Before source code check-in

Answer

After deployment

Question 9

What is 'Model Versioning' used for in an AI project?

Accepted Answer

Ensuring reproducibility and rollback. It allows tracking changes, rolling back to previous versions, and ensuring reproducibility.

Answer

Reducing model size

Answer

Improving training time

Answer

Increasing security

Question 10

Which THREE tasks are required for a 'Model Decommissioning' workflow?

Accepted Answer

Terminate serving infrastructure. Decommissioning requires archival, notification, and resource cleanup.

Answer

Ask developer for coffee

Answer

Delete all company records