Panel
Panel
Panel
Causality, Fairness and its Limitations
Session Chair:
Moderator:
Discussant:
Alix Dunn


Kosuke
Imai
Harvard University

Issa
Kohler-Hausmann
Yale Law School


Ricardo
Silva
Professor
Abstract
A panel focused on developments and applicability of causal modeling for algorithmic fairness. Given the increasing interest in the use of causality in machine learning (both in general and as a tool for bias mitigation), what is the potential for these approaches to be applied in the real world? What are the key challenges to putting these methods into practice?
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