Ethics and philosophy of AI applied to breast pathology

Abstract

This article addresses the ethical challenges of using AI in breast pathology detection, highlighting that algorithmic reliability is not sufficient without fairness. Based on Rawls' ideas of fairness, it discusses biases in data and algorithms that may affect accuracy in different populations. Furthermore, it criticizes dataism and proposes an approach that integrates ethical considerations into the development of medical AI applications from the outset.