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Safe AI for Data Scientists: Evidence, Documentation and Testing Regulators Accept

Uncertainty, Calibration and Abstention Thresholds

Quiz: Uncertainty, Calibration and Abstention Thresholds

Explainability Methods and Their Honest Limits

Quiz: Explainability Methods and Their Honest Limits

Validation by Someone Who Did Not Build the Model

Quiz: Validation by Someone Who Did Not Build the Model

Reproducibility: Seeds, Environments and Experiment Records

Quiz: Reproducibility: Seeds, Environments and Experiment Records

Writing the Model Card and the Technical File

Quiz: Writing the Model Card and the Technical File

Handover to Monitoring: What Production Needs From You

Quiz: Handover to Monitoring: What Production Needs From You

Final exam: Safe AI for Data Scientists: Evidence, Documentation and Testing Regulators Accept

2 of 2

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Quiz: Validation by Someone Who Did Not Build the Model

Safe AI for Data Scientists: Evidence, Documentation and Testing Regulators Accept
Validation by Someone Who Did Not Build the Model
Quiz: Validation by Someone Who Did Not Build the Model

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Question 1 of 5

1. Question

Why is independent validation important?

To save time
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To provide fresh perspective and sceptical review by someone with no stake in deployment
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To improve model accuracy
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To reduce computational cost
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Question 2 of 5

2. Question

What should an independent validator have access to?

Only the model predictions
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Only the accuracy metric
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All documentation: problem statement, data sources, metrics, fairness analysis and test results
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Only test set performance
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Question 3 of 5

3. Question

What makes validation a checkbox exercise rather than real validation?

Spending too much time
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Glancing at a summary report and approving without asking questions
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Validating on multiple datasets
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Asking for additional analysis
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Question 4 of 5

4. Question

Should an independent validator be involved in model development?

Yes, they need to understand the model
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No, independence means they should not have been involved in development
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Only if the model is high risk
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Yes, for better understanding
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Question 5 of 5

5. Question

What should documentation enable?

Faster model training
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Deployment without questions
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Independent assessment of whether development was sound
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Hiding controversial decisions
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