This AI Paper from Google Introduces a Causal Framework to Interpret Subgroup Fairness in Machine Learning Evaluations More Reliably
Understanding Subgroup Fairness in Machine Learning ML Evaluating fairness in machine learning often involves examining how models perform across different subgroups defined by attributes such as race, gender, or socioeconomic background. This evaluation is essential in contexts such as healthcare, where unequal model performance can lead to disparities in treatment recommendations or diagnostics. Subgroup-level performance…
