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- What are some common pitfalls that human evaluators and annotators may encounter when identifying bias in AI training data?
- What are some strategies for mitigating bias in AI training data through data curation and preprocessing?
- How can human evaluators and annotators be trained to recognize and address cultural and social biases in AI training data?
- What role do human evaluators and annotators play in ensuring that AI systems are transparent and explainable in their decision-making processes?
- Can you provide examples of successful programs or initiatives that have trained human evaluators and annotators to identify and mitigate bias in AI training data?
- How can human evaluators and annotators be trained to identify and address bias in AI systems that use natural language processing and text analysis?
- What are some best practices for human evaluators and annotators to follow when identifying and mitigating bias in AI training data related to sensitive topics such as healthcare and finance?
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