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Related Questions
- What are the key differences between active learning and passive learning in the context of bias reduction in data annotation?
- How does active learning help reduce bias in data annotation by focusing on uncertain or ambiguous data points?
- Can you provide an example of an active learning strategy for reducing bias in data annotation, such as uncertainty sampling or query-by-committee?
- How does active learning handle the trade-off between annotation cost and bias reduction in data annotation?
- What are some common challenges that arise when implementing active learning for bias reduction in data annotation, such as selecting the right query strategy or handling concept drift?
- Can you explain how active learning can be used to detect and mitigate bias in data annotation, such as through the use of fairness metrics or debiasing techniques?
- How does active learning compare to other methods for reducing bias in data annotation, such as data preprocessing or model-based debiasing?
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