Search Results for author:
Found 4 papers, 1 papers with code
A New Paradigm for Counterfactual Reasoning in Fairness and Recourse
The traditional paradigm for counterfactual reasoning in this literature is the interventional counterfactual, where hypothetical interventions are imagined and simulated.
Causal Dependence Plots
Since people often think causally about input-output dependence, CDPs can be powerful tools in the xAI or interpretable machine learning toolkit and contribute to applications like scientific machine learning and algorithmic fairness.
Counterfactuals for the Future
Counterfactuals are often described as 'retrospective,' focusing on hypothetical alternatives to a realized past.
Disaggregated Interventions to Reduce Inequality
We develop a disaggregated approach to tackling pre-existing disparities that relaxes the typical set of assumptions required for the use of social categories in structural causal models.
