Tara Capel - School of Informatics What problem are you trying to solve?Healthcare remains profoundly shaped by a gender data gap. Diagnostic tests, disease risk models and treatment protocols have historically been developed using data from cis-gender male bodies, positioning them as the ‘default’. As a result, people in marginalised bodies – women, and transgender, non-binary, genderqueer and genderfluid people – are routinely under-diagnosed, receive fewer diagnostic tests and are taken less seriously in medical encounters, particularly when presenting with chronic or hard-to-diagnose conditions. Digital health technologies risk amplifying this inequity. Many AI-driven and self-tracking tools are trained on incomplete or biased datasets and designed around normative assumptions of what health looks like. Optimisation is often framed as the goal of these tools and privileges regularity and efficiency, reproducing the same structural biases that have excluded gendered and bodily difference from biomedical understanding. What is your idea?To address this critical issue, our initiative aims to develop inclusive digital health applications that prioritise gender and body diversity in their foundational datasets and algorithms. By systematically including and analysing health data from marginalised groups, we aspire to redefine norms in health diagnostics and treatment to acknowledge and cater to variability rather than suppressing it. Our approach seeks to transform digital health tools into agents of equity, enabling personalised and accurate healthcare that elevates the dignity and validity of all gender identities in medical settings. This venture will involve collaboration with diverse communities, ensuring their voices and experiences shape the technology from the ground up, making it a truly inclusive platform. This article was published on 2025-11-17
