51 citations · 69 across the 12 of their papers we have counts for
5 papers · 1 filter
FADE: FAir Double Ensemble Learning for Observable and Counterfactual Outcomes
Alan Mishler, Edward Kennedy
Methods for building fair predictors often involve tradeoffs between fairness and accuracy and between different fairness criteria, but the nature of these tradeoffs varies. Recent…
Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing
Alessandro Fabris, Alan Mishler, Stefano Gottardi +4
We conduct an audit of pricing algorithms employed by companies in the Italian car insurance industry, primarily by gathering quotes through a popular comparison website. While ack…
Clustering Students and Inferring Skill Set Profiles with Skill Hierarchies
Alan Mishler, Rebecca Nugent
Cognitive diagnosis models (CDMs) are a popular tool for assessing students' mastery of sets of skills. Given a set of skills tested on an assessment, students are classified i…
When the Oracle Misleads: Modeling the Consequences of Using Observable Rather than Potential Outcomes in Risk Assessment Instruments
Alan Mishler, Niccolò Dalmasso
Risk Assessment Instruments (RAIs) are widely used to forecast adverse outcomes in domains such as healthcare and criminal justice. RAIs are commonly trained on observational data…
Comment on "Statistical Modeling: The Two Cultures" by Leo Breiman
Matteo Bonvini, Alan Mishler, Edward H. Kennedy
Motivated by Breiman's rousing 2001 paper on the "two cultures" in statistics, we consider the role that different modeling approaches play in causal inference. We discuss the rela…