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AI Bias Testing: Measuring Fairness With Numbers You Can Defend

Intersectional Analysis Beyond Single Attributes

Quiz: Intersectional Analysis Beyond Single Attributes

Bias in Generative Output: Representation and Stereotyping

Quiz: Bias in Generative Output: Representation and Stereotyping

Mitigation: Pre Processing, In Processing and Post Processing

Quiz: Mitigation: Pre Processing, In Processing and Post Processing

Trade Offs Between Accuracy, Fairness and Business Constraints

Quiz: Trade Offs Between Accuracy, Fairness and Business Constraints

Documenting a Bias Audit for Publication or Regulator Review

Quiz: Documenting a Bias Audit for Publication or Regulator Review

Ongoing Fairness Monitoring After Deployment

Quiz: Ongoing Fairness Monitoring After Deployment

Final exam: AI Bias Testing: Measuring Fairness With Numbers You Can Defend

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Quiz: Ongoing Fairness Monitoring After Deployment

AI Bias Testing: Measuring Fairness With Numbers You Can Defend
Ongoing Fairness Monitoring After Deployment
Quiz: Ongoing Fairness Monitoring After Deployment

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Question 1 of 5

1. Question

Why is continuous monitoring necessary for deployed AI systems according to the lesson?

To ensure that the system always operates at peak performance
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Because user behaviour and data distributions change over time
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To reduce the cost of system maintenance
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To comply with international data protection laws
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Question 2 of 5

2. Question

What should organisations do when fairness metrics deviate from established baselines?

Ignore the deviations until complaints arise
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Implement automatic alerts and re-evaluate system outcomes
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Conduct a full system overhaul immediately
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Report the issue to regulatory authorities
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Question 3 of 5

3. Question

Which of the following is mentioned as a component of effective ongoing monitoring frameworks?

Monthly review of demographic breakdowns in system outputs
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Annual re-evaluation of user feedback
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Quarterly assessment of data encryption protocols
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Continuous tracking of software version updates
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Question 4 of 5

4. Question

What is one purpose of implementing dashboard systems for fairness indicators?

To replace human decision-making entirely
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To display key fairness indicators in real-time
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To reduce the number of staff required for monitoring
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To store data for future regulatory audits
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Question 5 of 5

5. Question

What is a key benefit of maintaining strong monitoring practices according to the lesson?

The system becomes easier to update with new features
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The investment leads to reduced risk of regulatory penalties
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The system requires less computational power
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The cost of data storage decreases significantly
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