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Related Questions
- How can you use 'what if' prompts to identify potential blind spots in your training data?
- Can you describe a scenario where 'reverse' prompts helped you uncover bias in a model's output?
- How do you ensure that your 'what if' and 'reverse' prompts are effective in challenging assumptions and reducing bias?
- What are some common pitfalls to avoid when using 'what if' and 'reverse' prompts to address bias?
- Can you provide an example of how 'what if' prompts can help you identify and mitigate bias in a specific context?
- How do you measure the effectiveness of 'what if' and 'reverse' prompts in reducing bias in your models?
- What role do 'what if' and 'reverse' prompts play in ensuring that your models are fair and transparent?
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