AAISM Practice Test 4 — 10 Questions

Question 1

Which TWO factors are critical when assessing the risk of a new Generative AI use case?

Accepted Answer

The potential business impact if the system fails.. Business impact and data sensitivity are the foundational elements for risk assessment in AI.

Answer

The aesthetic of the user interface.

Answer

The office location of the developers.

Answer

The programming language used.

Question 2

Which TWO activities ensure 'AI Safety' in development?

Accepted Answer

Adversarial testing (red teaming).. Adversarial testing and rigorous documentation are key safety practices.

Answer

Using unmonitored cloud servers.

Answer

Increasing the amount of public data used.

Answer

Removing all encryption.

Question 3

Which THREE documents are vital for an AI audit trail?

Accepted Answer

Model validation and testing reports.. Model version, training set, and validation report are the three pillars of a reconstructible audit trail.

Answer

The office lease agreement.

Answer

A copy of the employee handbook.

Question 4

When using a 'Managed AI API' service, what is the best practice for handling API keys?

Accepted Answer

Store keys in a secure Secrets Manager. API keys should never be hardcoded; they should be stored in secrets managers like AWS Secrets Manager or Azure Key Vault.

Answer

Hardcode keys in the application source code

Answer

Email keys to team members for easy access

Answer

Embed keys in the public Git repository

Question 5

Which tool is best for managing 'Secrets' (like database passwords or API keys) used by your AI training pipeline?

Accepted Answer

HashiCorp Vault. Secrets management services (AWS Secrets Manager, HashiCorp Vault) are the secure way to manage credentials.

Answer

Hardcoded variables in the training script

Answer

A public Github repository

Answer

An Excel spreadsheet on a shared drive

Question 6

Which TWO of the following are primary risks associated with 'membership inference attacks' against an AI model?

Accepted Answer

Exposure of sensitive information about training data subjects.. Membership inference attacks aim to determine if a specific data point was used in the training set, risking privacy leakage.

Answer

Unauthorized modification of model weights.

Answer

Unauthorized access to the model training algorithm.

Answer

Complete system shutdown via resource exhaustion.

Question 7

What is the purpose of 'AI Model Inventory'?

Accepted Answer

To provide a central list of all AI assets for risk oversight.. An inventory tracks all models in production to ensure they are managed, monitored, and reviewed according to organizational policy.

Answer

To increase the speed of the training pipeline.

Answer

To reduce the number of GPUs used.

Answer

To automatically retrain all models.

Question 8

Which TWO components are essential for a robust AI Governance framework?

Accepted Answer

Defined roles and accountability structures.. Policies and clearly defined roles are the foundation of any governance system.

Answer

The company party schedule.

Answer

A list of all employee names.

Answer

The best-selling AI books.

Question 9

Which THREE items should be included in an 'AI Inventory'?

Accepted Answer

Unique model identifier and version.. Model version, owner, and risk rating are the core pieces of information needed to manage an AI portfolio.

Answer

The model's favorite color.

Answer

The developer's favorite food.

Question 10

An organization is using an LLM-based agent. What is the primary risk associated with 'indirect prompt injection' in this environment?

Accepted Answer

External data retrieved by the agent contains instructions that override system prompts.. Indirect prompt injection occurs when malicious data is embedded in a retrieved document that instructs the LLM to perform unintended actions.

Answer

The model produces hallucinatory facts.

Answer

The API key for the LLM is exposed in the code.

Answer

The training data includes PII of users.