Practice - Labeling Bias (Ground Truth Bias / Annotation Bias)
Practice Questions
Test your understanding with targeted questions
What is labeling bias?
💡 Hint: Think about human involvement in labeling data.
Give an example of labeling bias.
💡 Hint: Consider where data might come from and its history.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What kind of bias affects the labeling process in machine learning?
💡 Hint: Think about biases that occur during data preparation.
True or False: Labeling bias can only occur if the sensitive attributes are included in the model.
💡 Hint: Consider how the data is processed at the beginning.
1 more question available
Challenge Problems
Push your limits with advanced challenges
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.
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.
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Reference links
Supplementary resources to enhance your learning experience.