Fairness in AI refers to reducing or eliminating unjust biases so that a model's predictions do not systematically disadvantage, privilege, or otherwise treat certain demographic or protected groups differently. A model that produces equally reliable outcomes across groups is considered fair. Prediction latency, operational cost, and data compression are important technical considerations, but they are not what the term fairness addresses.
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AWS Certified AI Practitioner AIF-C01
Fundamentals of AI and ML
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