AAISM Practice Test 5 — 10 Questions

Question 1

Which THREE components are critical for an 'AI Incident Response' plan?

Accepted Answer

Communication channels with data scientists and legal teams.. An AI IR plan must account for model-specific issues like unexpected performance drops, bias, and adversarial attacks.

Answer

Requirements to publish all internal vulnerabilities publicly.

Answer

Automated deletion of all logs.

Question 2

Which of the following describes 'Model Integrity' risk?

Accepted Answer

The risk of the model weights being maliciously modified.. Model integrity risk refers to the potential for the model to be altered or behave in an unauthorized way, such as through poisoning or unauthorized weight updates.

Answer

The risk that the model will be too slow.

Answer

The risk of data being leaked during training.

Answer

The risk that users will stop using the app.

Question 3

An organization is performing threat modeling for a RAG (Retrieval-Augmented Generation) pipeline. Which specific vulnerability is unique to the retrieval component?

Accepted Answer

Database poisoning within the retrieved document index.. In RAG, if the search or retrieval index is manipulated, the LLM will generate answers based on attacker-supplied context.

Answer

Overfitting of the LLM on the training set.

Answer

Gradient-based evasion attacks on the LLM.

Answer

Prompt injection targeting the LLM model weights.

Question 4

A firm is drafting a policy for 'AI Use in Marketing'. Which element is most important to include to ensure alignment with existing data protection regulations?

Accepted Answer

Mandatory disclosure requirements when content is generated by AI.. Ensuring the AI system complies with transparency and privacy requirements (like GDPR) is foundational to AI governance policy.

Answer

A mandate to use only open-source AI models.

Answer

A list of all approved GPU hardware vendors.

Answer

The specific programming languages authorized for AI development.

Question 5

Which THREE elements are essential for 'AI Governance'?

Accepted Answer

Defined AI ethics and safety policies.. AI governance requires clear policies, oversight committees, and defined risk frameworks.

Answer

Access to all employees' private emails.

Answer

A mandate to use the most expensive GPUs available.

Question 6

When evaluating AI security, 'Model Drift' refers to performance degradation over time. Which tool would a practitioner use to detect drift in a production environment?

Accepted Answer

Amazon SageMaker Model Monitor. Model monitoring tools track statistical properties of features and predictions to identify drift.

Answer

AWS Config

Answer

Amazon GuardDuty

Answer

AWS CloudTrail

Question 7

Which TWO of the following are effective methods for monitoring and detecting AI security incidents in a cloud environment?

Accepted Answer

Ingesting model inference logs into a SIEM. Centralized logging (e.g., CloudWatch, Azure Monitor) and anomaly detection are critical for identifying unexpected model interactions.

Answer

Disabling logging to reduce cloud spend

Answer

Using standard database backup schedules

Answer

Hardcoding API credentials in application code

Question 8

Which of the following is a 'Human-in-the-Loop' (HITL) control used for AI risk management?

Accepted Answer

Requiring human approval for high-risk model outputs. HITL involves human review of model decisions before they are finalized or acted upon, especially for high-stakes decisions.

Answer

Using only open-source libraries

Answer

Deploying the model to a public server

Answer

Automating all model output without review

Question 9

Which TWO measures are most effective in reducing the risk of 'Hallucinations' in LLM systems?

Accepted Answer

Using Retrieval-Augmented Generation (RAG).. RAG and Grounding ensure the model relies on external, verified context rather than its internal probabilistic memory.

Answer

Training the model on larger public internet datasets.

Answer

Removing all punctuation from the input.

Answer

Increasing the model's temperature parameter to 2.0.

Question 10

You are managing an AI project and notice the model is performing poorly on a subset of data representing a protected class. What is the correct next step in the risk assessment process?

Accepted Answer

Investigate the data representation and training balance for that subgroup.. Performing a root cause analysis on the data used to train that specific segment is the correct diagnostic step.

Answer

Immediately delete all training data.

Answer

Dismiss the finding as a minor edge case.

Answer

Replace the model architecture with a simpler one.