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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is labeling bias?
💡 Hint: Think about human involvement in labeling data.
Question 2
Easy
Give an example of labeling bias.
💡 Hint: Consider where data might come from and its history.
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
What kind of bias affects the labeling process in machine learning?
- Labeling Bias
- Algorithmic Bias
- Evaluation Bias
💡 Hint: Think about biases that occur during data preparation.
Question 2
True or False: Labeling bias can only occur if the sensitive attributes are included in the model.
- True
- False
💡 Hint: Consider how the data is processed at the beginning.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Analyze a hypothetical scenario where a facial recognition system misclassifies individuals from different ethnic backgrounds due to biased labeling. Propose a detailed strategy to mitigate this bias.
💡 Hint: Consider strategies that target both human judgment and data diversity.
Question 2
Discuss the ramifications of using historical hiring data that contains biases for training an AI-based recruitment tool. What measures could be implemented to avoid perpetuating these biases?
💡 Hint: Think about what happens to data from the past.
Challenge and get performance evaluation