A leading rheumatologist teamed up with an AI specialist to help with a systematic review of lupus research, a condition of which 90% of patients are women. Together, they revealed the deep-rooted biases in research methodologies - and the machine learning models that underpin them.

Professor Coziana Ciurtin (UCL) and Mirela Gyurova (Kubrick) share the story behind their GenAI tool which can revolutionise underfunded and underexplored areas of medical research, including identifying ML-enforced biases.

When gender and ethnic disparities in healthcare persist, what responsibilities do data professionals have in shaping ethical, impactful AI? And how can partnerships between industry and academia unlock new standards for evidence, equity, and trust in ML?

For anyone building, using, or regulating AI, this session will challenge assumptions and make the case for responsible, cross-sector innovation.

Powered by Women in Data®