Decoding Bias: Why Women Must Be at the Table for the AI Revolution in Health
Artificial Intelligence is currently being “taught” how to practice medicine. But if the textbooks it learns from are missing data on 51% of the population, we aren’t building a smarter future—we are automating the biases of the past.
A landmark collaboration between Women at the Table and FemTechnology, our latest paper—AI & Women’s Health—isn’t just a report; it’s a call for a new “Social Contract for Data.”
For too long, female biology has been treated as a “deviation from the norm.” This exclusion has created a massive gender data gap that now threatens to be baked into the very algorithms that will decide who gets diagnosed, who gets treated, and who gets insured.
- Gender-Responsive AI: Moving beyond binary data to understand the complex biological and social determinants of health.
- A New Regulatory Framework: Ensuring that AI tools are audited for gender bias before they reach the clinical bedside.
- Structural Inclusion: Ensuring women are not just “users” of these tools, but the architects of the systems.
This research was partially funded by the Swiss FDFA and the Friedrich Naumann Foundation for Freedom Human Rights Hub.