Abstract

It appears to be something wrong if a person’s health is related to gender. Indeed, we might have continued to link this dependency (health-gender) to other factors—such as education or income—had it not been for the use of artificial intelligence-based systems in medicine and healthcare, which made us more aware of a broader picture of how medical research and practice has not taken male and female bodies into account equally. Nonetheless, AI has to be trustworthy, and for that purpose, it shall be lawful, ethical, and robust. But how lawful and ethical can it be if it leaves half of humanity out of the picture? Hence the focus of this chapter is to address how medical AI could positively impact the achievement of gender equality as a Sustainable Development Goal (SDG). In particular, we use several use cases to highlight how medical AI applications have made it evident that there is an enormous data gap between male and female sex involvement in clinical trials, disease treatment, and other medical therapies and that this data gap is the reason why so many AI applications are biased, limited, and inefficient. Filling this gap would mean improving and increasing data generation that would reflect particularities and specificities of female bodies and enable female representation in training algorithms.