The document discusses the proposal of a solution to balance fairness and utility in classification tasks by leveraging aleatoric uncertainty. It introduces a model to improve fairness when aleatoric uncertainty is high and utility elsewhere. The approach involves distributional intervention, decoupling of uncertainty types, and optimizing the fairness-utility trade-off. The theoretical guarantees for improving the trade-off are also presented in the document.