AAIA Multiple Select — 30 Questions

Question 1

When conducting an audit, which THREE of the following represent potential 'Model Risk' areas that require documentation?

Accepted Answer

Susceptibility to adversarial attacks. Adversarial vulnerability, data drift, and bias are three primary risks requiring documentation in an AI audit report.

Answer

The color of the server racks

Answer

The speed of the local internet connection

Question 2

An auditor is evaluating the 'Model Monitoring' dashboard. Which TWO items should the dashboard display to alert the team of potential issues?

Accepted Answer

Real-time model accuracy metrics. Data drift and prediction accuracy are the two most critical metrics for a model monitor.

Answer

The model developer's vacation schedule

Answer

Public stock prices of the firm

Answer

Office building temperature

Question 3

Which TWO of the following are essential when performing an 'AI Risk Assessment'?

Accepted Answer

Assessing the likelihood and severity of identified risks. An assessment must identify both technical risks and potential impacts on stakeholders.

Answer

Listing the names of the team members' families

Answer

Choosing the best coffee brand for the office

Answer

Selecting the color scheme for the model's dashboard

Question 4

Which TWO of the following are typical 'Model Risk Management' (MRM) pillars?

Accepted Answer

Independent model validation. MRM is structured around independent validation and continuous monitoring.

Answer

Designing office holiday parties

Answer

Negotiating salaries for the data scientists

Answer

Public relations management

Question 5

Which TWO of the following are legitimate 'AI Governance' concerns regarding third-party AI service providers (SaaS)?

Accepted Answer

Data residency and compliance with local regulations. Auditors must ensure that third-party AI tools comply with internal data handling standards and that the vendor's own governance is adequate.

Answer

The programming language used by the vendor

Answer

Vendor's model update and retraining frequency

Answer

The physical location of the vendor's corporate office

Question 6

When selecting testing techniques for an AI model, which THREE are considered 'Model-Agnostic'?

Accepted Answer

SHAP (SHapley Additive exPlanations). LIME, SHAP, and Partial Dependence Plots (PDPs) are model-agnostic methods that work with any ML model.

Answer

Neural network weight pruning

Answer

Linear regression coefficients

Question 7

Which THREE criteria are essential when selecting an AI deployment strategy?

Accepted Answer

Service Level Agreements (SLAs). Strategy must balance risk, speed, and resource availability.

Answer

Color of the UI

Answer

Number of coffee machines

Question 8

When auditing a model deployment pipeline, which TWO aspects are critical to verify to ensure compliance with AI governance frameworks?

Accepted Answer

Validation of data processing against privacy policies. Governance requires both reproducibility and data privacy/security checks.

Answer

Whether the team uses a specific cloud provider

Answer

The speed of the training job

Answer

Usage of proprietary algorithms only

Question 9

When documenting audit findings for an AI system, which TWO of the following are critical to include to ensure the audit can be replicated?

Accepted Answer

Specific Git commit SHA for the model code. Version control information and the exact dataset version are essential for reproducing the audit results.

Answer

The office location of the data scientists

Answer

The brand of the coffee machine used

Answer

The developer's personal email address

Question 10

Which THREE factors should an auditor consider when evaluating the suitability of an AI model for production?

Accepted Answer

Inference latency and throughput. Accuracy, fairness metrics, and latency/throughput are standard KPIs for production readiness.

Answer

Developer age demographics

Answer

Operating system color schemes

Question 11

When documenting findings, which THREE elements should be included for each finding?

Accepted Answer

The root cause. The condition, the root cause, and the recommendation are essential components of an audit finding.

Answer

The font size used in the report

Answer

The names of all employees who disagreed

Question 12

Which TWO of the following are examples of AI governance 'Inputs'?

Accepted Answer

Internal AI Policy and guidelines. Inputs include regulatory requirements and internal policy documents.

Answer

A photograph of the company founder

Answer

The company's social media password

Answer

The office printer manual

Question 13

Which THREE of the following are potential risks associated with AI model 'Drift' that an auditor must account for?

Accepted Answer

Bias against specific demographic groups that emerged post-deployment. Drift impacts operational accuracy, fairness, and compliance, making it a critical governance risk.

Answer

Increased electricity consumption of servers

Answer

Inability to access the source code of the model

Question 14

Which TWO methods are commonly used by auditors to verify the 'Provenance' of training data?

Accepted Answer

Reviewing data lineage logs in the metadata store. Hashing files and maintaining lineage logs are standard technical methods to verify data provenance.

Answer

Watching the training video

Answer

Interviewing the janitorial staff

Answer

Checking if the model is open source

Question 15

Which TWO monitoring tools are typically used to detect 'Data Drift' in production pipelines?

Accepted Answer

AWS SageMaker Model Monitor. AWS SageMaker Model Monitor and Google Cloud Vertex AI Model Monitoring are industry standard tools for drift detection.

Answer

Web Browser

Answer

Microsoft Excel

Answer

Adobe Photoshop

Question 16

When scoping an AI audit engagement, which TWO of the following documents should the auditor request to understand the AI model's governance structure?

Accepted Answer

Technical system architecture documentation. Model Cards and technical documentation provide the necessary governance and implementation context for an auditor.

Answer

Public social media posts

Answer

Company marketing brochures

Answer

Developer salary structures

Question 17

An auditor is evaluating the data pipeline security. Which THREE controls should be verified?

Accepted Answer

Full audit log of data provenance. Access control, encryption at rest, and data provenance are standard security controls for AI data pipelines.

Answer

The number of lines of code in the pipeline

Answer

Office access badge logs

Question 18

Which TWO of the following are core components of an AI incident response strategy?

Accepted Answer

Defined communication protocols for internal and external stakeholders. Incident response requires both technical preparation and clear communication channels to handle potential AI failures.

Answer

Marketing campaigns for AI product launches

Answer

Software license management for all developers

Answer

Automated email server maintenance

Question 19

Which TWO metrics provide the best insights into 'Model Quality' during an audit?

Accepted Answer

Recall score. Precision and Recall are fundamental metrics for assessing the quality of classification models.

Answer

Disk space usage

Answer

Number of server restarts

Answer

Team's average coffee intake

Question 20

Which TWO of the following are examples of 'Data Leakage' that an auditor should look for in a pipeline?

Accepted Answer

Training on test data. Target leakage and future data leakage are primary types of data leakage in AI pipelines.

Answer

Using cloud-based storage

Answer

Documenting model parameters

Answer

Using open-source libraries