Tips for Building Ethical and Effective AI Models
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Think carefully about selecting a target variable that aligns with a clear business use case where model outputs can inform decisions.
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Deal thoughtfully with imbalanced training data rather than blindly oversampling minority groups.
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Test models on real-world data that reflects what the model will see in production.
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Choose evaluation metrics that measure performance in a way that is meaningful to the business.
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Carefully consider when model scores do or do not provide value in decision making.