Vulnerability in the age of artificial intelligence: addressing gender bias in healthcare

Abstract

Gender bias represent a source of vulnerability in current clinical practice as they can harm patients, especially those identified as gender minorities. This risk is increased in the age of AI-powered healthcare, which calls for redefining vulnerability and strategies to prevent algorithms from exacerbating already existing inequalities. To this end, we analyse the solutions proposed by the European Union's recent AI Act. Moreover, we consider whether AI itself can be a solution to these issues.