Modern Medicines and treatments can be improved with the progression of AI in medicine by discovering new drugs, personalising treatments, and speeding up chemical trials. But if the racial exclusion common in biomedical research seeps into the data behind AI there’s a risk that these medicines won’t be effective for everyone.
The advent of AI promises to revolutionise the way we think about medicine and healthcare, but who do we hold accountable when automated procedures go awry? In this talk, Varoon focuses on the lack of affordable medicines within healthcare and the concerns over racial bias being brought into the healthcare system.
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Using the example of machine learning in medicine as an example, Rachel Thomas examines examples of racial bias within the AI technologies driving modern-day medicines and treatments. Rachel Thomas argues that whilst the diversity of your data set, and performance of your model across different demographic groups is important, this is only a narrow slice […]
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Talk by Rachel Thomas on the prevalence of bias within AI-based technology used in medicine. AI has the potential to remove human biases in the healthcare system, however its integration within medicine could also amplify the existing biases.
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A short video examining the lack of inclusion within clinical biomedical research, and the consequence this has on the effectiveness of the treatments and medicines for non-white patients. Lack of research on minority patients means that we do not understand the racial differences in drug response, and so approved medical treatments are excluding a huge […]
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