Bias Detection and Mitigation Quiz

Quiz covering Responsible AI in MLOps

Questions in this quiz

A preview of the 5 questions covered. Start the quiz above to answer them, check your score, and read the explanations.

1. 1

   Which of the following is the most direct way to detect bias in a machine learning model's predictions?

2. 2

   When addressing bias in a dataset, what does 're-weighting' involve?

3. 3

   A model is showing high accuracy overall but consistently fails for a specific minority group. Which mitigation strategy is best suited to address this during the post-processing phase?

4. 4

   Why is 'blindness' (removing sensitive attributes like race or gender from the input) often ineffective at preventing bias in machine learning models?

5. 5

   In the context of the 'Fairness-Accuracy Trade-off,' which statement best describes the challenge faced by MLOps engineers?