Mohamed Abdalla, Quantifying (Un)Fairness

The Centre for Ethics at the University of Torontois an interdisciplinary centre aimed at advancing research and teaching in the field of ethics, broadly defined. The Centre seeks to bring together the theoretical and practical knowledge of diverse scholars, students, public servants and social leaders in order to increase understanding of the ethical dimensions of individual, social, and political life.

Centre for Ethics, University of Toronto

Mohamed Abdalla joins the Centre for Ethics for a talk on "Quantifying (Un)Fairness."

Quantifying (Un)FairnessIn the machine learning fairness literature, the majority of fairness definitions are formalized for the binary case. This binary formalization allows for simple hypothetical demonstrations of the fairness definitions and provides researchers the ability to prove theorems. However, in clinical settings, the binary case is often too simple. As a consequence, we must expand machine learning definitions of fairness beyond these binary formulations. In this work, we analyze different ways of expanding fairness definitions beyond the binary case, highlighting edge cases where such expansions do not work as expected. We perform empirical analysis on a clinical task to assess how likely each edge case is for non-binary expansion, and consider the clinical feasibility and ramifications of such decisions.Mohamed AbdallaUniversity of TorontoComputer Science04:00 PM - 05:30 PMCentre for Ethics, University of Toronto200 Larkin

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Mohamed Abdalla, Quantifying (Un)Fairness

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Mohamed Abdalla, Quantifying (Un)Fairness

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