AAISM Practice Test 14 — 15 Questions

Question 1

What does 'Model Explainability' (XAI) primarily support in governance?

Accepted Answer

Transparency, trust, and regulatory compliance.. XAI supports transparency and trust by allowing humans to understand the 'why' behind model outputs.

Answer

Lower infrastructure costs.

Answer

Hardware security.

Answer

Increased training speed.

Question 2

Which THREE activities should be included in an AI Security Governance Program to effectively manage model supply chain risks?

Accepted Answer

Verifying the integrity and origin of pre-trained models via digital signatures.. Managing supply chain risks requires provenance, dependency scanning, and license verification to ensure security and compliance.

Answer

Conducting monthly performance benchmarking of model inference speed.

Answer

Increasing the budget for AI model research and development.

Question 3

Which phase of the AI Lifecycle is most critical for 'Bias Detection'?

Accepted Answer

Model testing and evaluation.. Testing and evaluation (pre-deployment) is the primary window for detecting and mitigating bias before it impacts users.

Answer

Contract negotiation with vendors.

Answer

Model decommissioning.

Answer

Data center power-up.

Question 4

An AI security program manager is assessing AI risks. Which tool provides the most centralized oversight for AI model compliance?

Accepted Answer

An enterprise GRC platform with AI modules.. A GRC (Governance, Risk, and Compliance) platform configured for AI enables systematic tracking of risks and policy adherence.

Answer

A local Python script for model testing.

Answer

A public open-source project management board.

Answer

A standard spreadsheet file.

Question 5

Which document outlines the 'Roles and Responsibilities' for AI security?

Accepted Answer

The AI Governance Charter.. The AI Governance Charter or Policy defines the organizational structure for AI risk management.

Answer

The printer configuration manual.

Answer

A software license file.

Answer

The company holiday calendar.

Question 6

Which activity is part of 'Ongoing AI Monitoring'?

Accepted Answer

Monitoring model performance and risk metrics.. Continuous performance review ensures that the AI system remains within its defined risk appetite and operational parameters.

Answer

Choosing the AI vendor.

Answer

Installing the server OS.

Answer

Initial software design review.

Question 7

When designing a secure AI development lifecycle (SDLC), which of the following is an essential governance activity during the 'Model Deployment' phase?

Accepted Answer

Finalizing the Model Card to document intended use, limitations, and security parameters.. A 'Model Card' is a documentation standard that captures risk parameters and intended use, essential for post-deployment governance.

Answer

Running a brute-force attack on the model API.

Answer

Updating the GPU drivers on the inference servers.

Answer

Resetting the encryption keys for the production database.

Answer

Removing all training data from the production environment.

Question 8

Which TWO aspects of 'Transparency' are most important for AI stakeholders?

Accepted Answer

Disclosing the use of AI to the end-user.. Explaining the logic behind outputs and disclosing that the user is interacting with an AI are key transparency requirements.

Answer

Providing a list of all server rack IDs.

Answer

Publishing the model's marketing budget.

Answer

Sharing the home addresses of developers.

Question 9

Which TWO reporting formats are effective for executive AI oversight?

Accepted Answer

Executive summaries of AI performance and risk.. Risk heatmaps and executive summaries provide the high-level view required by management.

Answer

Full source code printouts.

Answer

Raw system logs in text files.

Answer

A list of all server IP addresses.

Question 10

Which TWO of the following are essential components of an 'AI Security Policy' in an enterprise?

Accepted Answer

Mandatory security and red-teaming testing for high-risk models. A robust policy must define acceptable use cases and mandate security testing (like red teaming) for all AI assets.

Answer

Requirement to use only proprietary AI models

Answer

Definition of hardware refresh cycles for data centers

Answer

Requirement to disable all audit logs to protect privacy

Question 11

Which TWO areas should be covered by an AI procurement policy?

Accepted Answer

Contractual clauses for data privacy and IP protection.. Vendor security assessment and contractual data usage clauses are critical for third-party AI risk.

Answer

The color of the vendor's logo.

Answer

The vendor's choice of office furniture.

Answer

The number of employees at the vendor.

Question 12

When securing an AI-driven chatbot, which THREE of the following are recommended practices to mitigate 'Prompt Injection' vulnerabilities?

Accepted Answer

Perform input sanitization on all user-submitted text. The primary defenses involve rigorous input validation, context separation between instructions and data, and using specialized output filters.

Answer

Store model training data in plaintext

Answer

Increase the model's temperature parameter

Question 13

An organization uses IBM watsonx.ai to manage model governance. Which tool is primarily used to track 'FactSheets' for model lineage and auditability?

Accepted Answer

FactSheets. The IBM watsonx.ai Governance module uses FactSheets to automatically capture and document the lifecycle, lineage, and validation status of models.

Answer

AutoAI Experiment Tracker

Answer

Pipeline Orchestrator

Answer

Model Risk Management (MRM) dashboard

Question 14

An AI security team needs to ensure that internal AI tools comply with the organization's 'Human-in-the-Loop' policy. Which architectural control best enforces this governance requirement?

Accepted Answer

Integrating a mandatory 'human approval' task within the business logic workflow of the AI orchestration layer.. Implementing an approval gate in the workflow ensures that critical decisions made by AI are reviewed by humans, satisfying the governance policy.

Answer

Enabling role-based access control (RBAC) in the AI model management system.

Answer

Configuring audit logs for all AI interactions.

Answer

Updating the model weights to penalize autonomous decision-making.

Answer

Applying data loss prevention (DLP) rules to the model training dataset.

Question 15

What is the benefit of 'Versioning' your AI models in a production environment?

Accepted Answer

Enables rapid rollback to previous models. Versioning enables rapid rollback to a known good state if a new version is found to be insecure or perform poorly.

Answer

Reduces the size of the model file

Answer

Increases API speed

Answer

Automatically detects prompt injection