= Fairness (machine learning)
{wiki=Fairness_(machine_learning)}
Fairness in machine learning refers to the principles and practices aimed at ensuring that machine learning models operate equitably and do not produce biased or discriminatory outcomes against individuals or groups based on sensitive attributes such as race, gender, age, religion, or disability. As machine learning is increasingly used in high-stakes areas like hiring, lending, healthcare, and criminal justice, ensuring fairness is critical to preventing harm and ensuring trust in these systems.
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