In a scenario where a credit scoring AI model is criticized for being biased against certain demographic groups, how would you approach investigating and potentially rectifying this issue?
- Retrain the model with more data from the underrepresented groups.
- Ignore the criticism as it might be baseless.
- Conduct an audit of the training data and model features.
- Refuse any changes as it might affect model performance.
When faced with bias concerns, a responsible approach is to conduct an audit of the training data and model features to identify and mitigate bias. Ignoring the issue or refusing changes is not recommended, and simply retraining with more data may not address the root cause of bias.
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