Fairness Metrics in Machine Learning

Fairness metrics in machine learning are tools used to evaluate how unbiased and equitable a model's predictions are across different groups of people. These metrics assess whether a model treats all individuals fairly, regardless of attributes like race, gender, or age. By analyzing outcomes, such as accuracy or error rates, for various demographic groups, fairness metrics help identify and mitigate potential discrimination in AI systems, ensuring that technology benefits everyone fairly and doesn't reinforce existing inequalities.