14hs: Palestra William La Cava
15:30hs: Mesa Redonda sobre o tema Explicabilidade e Equidade
The field of Fair Machine Learning attempts to guarantee, in some specific sense, that a machine learning model does not cause harm to a particular subpopulation. Predictive models are increasingly used to support clinical decision making, giving rise to many fairness concerns.
This talk will break down some of the opportunities and challenges for fair machine learning in health, especially the role of group-wise calibration and intersectional group definitions.
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