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AI Training for Internal Auditors: Auditing Models, Data and Decisions With Confidence

What Internal Audit Can and Cannot Assure About AI

Quiz: What Internal Audit Can and Cannot Assure About AI

Building AI Into the Annual Audit Plan

Quiz: Building AI Into the Annual Audit Plan

Understanding the Model Life Cycle Well Enough to Audit It

Quiz: Understanding the Model Life Cycle Well Enough to Audit It

Scoping an AI Audit: System, Process or Whole Programme

Quiz: Scoping an AI Audit: System, Process or Whole Programme

Auditing Governance: Policy, Roles and Approval Records

Quiz: Auditing Governance: Policy, Roles and Approval Records

Auditing Data: Sourcing, Quality, Consent and Retention

Quiz: Auditing Data: Sourcing, Quality, Consent and Retention

Auditing Model Development, Testing and Validation Records

Quiz: Auditing Model Development, Testing and Validation Records

Auditing Deployment Controls, Access and Change Management

Quiz: Auditing Deployment Controls, Access and Change Management

Auditing Monitoring, Drift Detection and Alert Response

Quiz: Auditing Monitoring, Drift Detection and Alert Response

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Quiz: Auditing Monitoring, Drift Detection and Alert Response

AI Training for Internal Auditors: Auditing Models, Data and Decisions With Confidence
Auditing Monitoring, Drift Detection and Alert Response
Quiz: Auditing Monitoring, Drift Detection and Alert Response

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Question 1 of 5

1. Question

What is the minimum set of metrics that should be monitored in production?

Only technical metrics like latency and error rate
Correct Incorrect Correct answer

The same metrics used to evaluate the model before deployment, such as accuracy and recall
Correct Incorrect Correct answer

Only the number of decisions made per day
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Only cost and speed
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Question 2 of 5

2. Question

What is model drift in production?

Bugs in the code that processes model outputs
Correct Incorrect Correct answer

Changes in the distributions of model inputs or outputs from what the training data represented
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Normal day-to-day variation in model decisions
Correct Incorrect Correct answer

Disagreement among team members about model strategy
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Correct / 1 Points

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Question 3 of 5

3. Question

What is a control failure related to drift detection?

Detecting drift too quickly
Correct Incorrect Correct answer

Implementing drift detection but not acting on alerts when they are triggered
Correct Incorrect Correct answer

Tracking too many drift metrics
Correct Incorrect Correct answer

Using statistical methods instead of rule-based alerts
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Correct / 1 Points

Incorrect / 1 Points
Question 4 of 5

4. Question

Why is fairness monitoring in production particularly important?

It is required only by European regulators
Correct Incorrect Correct answer

Fairness drift often affects vulnerable populations first and is hardest to detect when monitoring only overall metrics
Correct Incorrect Correct answer

It is only needed for hiring systems
Correct Incorrect Correct answer

It helps improve model speed
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Question 5 of 5

5. Question

What should you audit about model retraining procedures?

Only the cost of retraining
Correct Incorrect Correct answer

Who decides when to retrain, how frequently, and whether retraining follows the same development and validation procedures as the original model
Correct Incorrect Correct answer

Only how fast retraining happens
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Only the volume of new data available
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