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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is subgroup performance analysis?
💡 Hint: Focus on demographic groups in your response.
Question 2
Easy
Define bias in the context of AI.
💡 Hint: It relates to fairness in model predictions.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
Why is it important to analyze performance metrics for subgroups?
- To reduce overall accuracy
- To ensure fairness
- To increase complexity
💡 Hint: Consider which answers relate to equitable outcomes.
Question 2
True or False: Subgroup performance analysis can reveal biases not evident in overall model accuracy.
- True
- False
💡 Hint: Think about how different groups may be affected.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given an AI model for loan predictions, how would you approach modifying the model if you find it disproportionately denying loans to applicants from specific demographics, despite high overall accuracy?
💡 Hint: Think about the entire model lifecycle - from data collection to deployment.
Question 2
Critically analyze an AI model used for hiring that shows a high accuracy rate but poor performance on female applicants. What steps would you suggest to improve its fairness?
💡 Hint: Consider how different aspects of the model can contribute to these performance disparities.
Challenge and get performance evaluation