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Related Questions
- What role does data quality play in ensuring the fairness of machine learning models?
- How can biased data be identified and addressed during the curation process?
- What are some common pitfalls to avoid when annotating data for fairness audits?
- Can you explain the concept of 'representation bias' in the context of data curation?
- How does data curation impact the generalizability of machine learning models?
- What are some strategies for reducing bias in data annotation processes?
- Can you discuss the relationship between data curation and the concept of 'adversarial examples'?
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