Recently, we held another of our webinar and were delighted to welcome Nyalleng Moorosi from the Distributed AI Research Institute (DAIR) to explore some discussions around understanding how we can build models which centre populations often regarded as peripheral. Thank you to all who managed to attend the webinar series and made it an interactive platform with lots of questions and ideas discussed. You can catch the full video recording below 👇
The talk was on "Documenting Health Datasets - Incentives, Transparency, Audits and Inclusion". Nyalleng has discussed how machine learning in healthcare has shown promise, particularly in diagnostic fields like radiology but it also comes with challenges and bias. Concerns arise when AI fail to allocate services equitably or infer social categories, emphasising the need for data documentation, incentivising detailed data artifacts, and considering diversity in ML for health systems. Watch the youtube video to listen to the whole talk.
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