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Related Questions
- How can biased language in training data affect the performance of AI models?
- What are some common data collection methods that can perpetuate cultural and linguistic biases in AI models?
- Can you provide examples of how AI models may reflect and amplify existing social biases present in the data used to train them?
- What strategies can be employed to mitigate cultural and linguistic biases in AI model development?
- How can data preprocessing techniques, such as tokenization and normalization, impact the representation of underrepresented groups in AI models?
- What role do annotators and data curators play in introducing biases into AI models through data collection and labeling?
- Can you discuss the importance of diverse and representative datasets in training AI models that are fair and unbiased?
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