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Related Questions
- How does data annotation impact the accuracy of machine learning models in detecting biases?
- What are some common biases that can be introduced during data annotation and how can they be mitigated?
- Can you explain the concept of annotation drift and its effects on model performance and fairness?
- How does the quality of data annotation affect the performance of fairness metrics in machine learning models?
- What are some strategies for ensuring that data annotation is done in a way that promotes fairness and reduces bias?
- Can you provide examples of successful data annotation approaches that have led to fair and unbiased machine learning models?
- How can data annotation be used to identify and address biases in machine learning models that are already in production?
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