Transforming women’s health with generative AI
Kubrick partnered with Women in Data® and University College London (UCL) to uncover bias and transform outcomes for women’s health, using generative AI.
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The challenge
A leading professor in autoimmune disease research at UCL wanted to test the hypothesis that most studies on Systemic Lupus Erythematosus (SLE), which disproportionately affect women, don’t adequately address the risk of sex bias in their methodologies when using Machine Learning.
In partnership with Women in Data®, Kubrick provided the voluntary expertise of two of their Generative AI specialists to help expedite and improve the systematic review processes to uncover sources of bias.
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The approach
Kubrick’s consultants created a proof of concept which they scaled to a Minimum Viable Product (MVP) to test and develop a GenAI tool using OpenAI GPT-3.5 Turbo LLM.
They worked with their client to align their technology to domain protocols to augment highly manual processes, including sourcing and vetting papers for eligibility, scoring papers on their proficiency in addressing and remediating potential sex bias, and scoring papers in their proficiency to follow Machine Learning best practice to remediate potential bias.
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The impact
The MVP sourced and scored 160 papers with a run-time of two minutes per paper for assessment, demonstrating the ability to reduce the workload of researchers from weeks to days.
Kubrick provided a comprehensive report on the tool and the development process to ensure explainability and transparency of GenAI to enhance trust and encourage human oversight.
Kubrick are now working with Women in Data® to scale access to the tool for other women’s health initiatives.
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