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Can data be labeled consistently?
Can data be labeled consistently?
- Labeling bias occurs when data labels are inconsistently applied by different annotators, which can affect fairness and model accuracy. This can happen when: Label definitions are unclear.
- Annotators interpret criteria differently.
- Subjective judgments influence labeling decisions.
If you answered No then you are at risk
If you are not sure, then you might be at risk too
Recommendations
- Clarify labeling requirements, ensuring that label definitions are precise and consistent from the start.
- Train annotators and provide clear guidelines to reduce subjectivity.
- Review labeling processes: regularly check annotations for consistency and accuracy.