Fairness focuses on whether a model's predictions treat individuals and groups equitably-avoiding systematic favoritism or discrimination toward protected or sensitive classes. High overall accuracy, lower latency, or reduced data requirements do not guarantee that outcomes are distributed fairly across sub-populations, so they are not the core meaning of fairness in AI/ML.
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Fundamentals of AI and ML
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