AI tools used in healthcare can carry hidden biases, sometimes performing less accurately for women, ethnic minorities, or other underrepresented groups. But knowing this risk exists in general is one thing. Being able to check whether a specific tool, in a specific clinical area, has documented bias issues is another, and that’s exactly the gap the AEQUITAS Database was built to fill.
The AEQUITAS Database is a structured, digital repository that systematically collects, organises, and provides access to evidence on gender and racial bias in biomedical AI. Rather than leaving healthcare professionals, researchers, and policymakers to piece together scattered studies and reports, it brings this dispersed evidence together into one coherent, accessible knowledge base.
The database is publicly accessible through the AEQUITAS project website, and it was built with a user-oriented approach, meaning both technical and non-technical users can navigate it effectively.
Built for multiple audiences
The Database was designed to serve several groups at once, each with different needs. For healthcare professionals, it’s a resource for identifying potential biases in AI-based diagnostic and decision-support tools, improving patient-centred care, and reducing the risk of misdiagnosis. For civil society organisations, it supports awareness-raising and advocacy for fair, inclusive healthcare systems. And for researchers and policymakers, it feeds into further scientific investigation, the development of clinical guidelines, and regulatory oversight at European level.
A practical tool
The Database is designed to be used, not just consulted occasionally. Before adopting a new AI tool, healthcare professionals can search for entries related to its disease area to check whether bias has been documented in similar tools. When an AI system produces unexpected outputs, the Database can help determine whether it’s a known pattern rather than an isolated anomaly. And when caring for patients from underrepresented groups, it can help clinicians understand whether the tools involved in their care carry documented disparities relevant to that patient’s profile.
The Database is also a living resource that will grow as new evidence becomes available. The more healthcare professionals, researchers, and organisations engage with it, the more valuable it becomes for everyone.