Maria De-Arteaga, Riccardo Fogliato, Alexandra Chouldechova

This blog post is based on our conference paper at CHI 2020 and workshop paper at the Fair and Responsible AI workshop.

Background

Risk assessment tools are increasingly being incorporated into expert decision-making pipelines across domains such as criminal justice, education, health, and public services [1,2,3,4]. These tools, which range from simple regressions to more complex machine learning models, distill available information on a given case into a risk score reflecting the likelihood of one or more adverse outcomes.

Most often, the tools are not meant to make autonomous decisions, but rather to provide a…

Riccardo Fogliato

PhD Student in Statistics @ Carnegie Mellon University & Research Fellow @ Partnership on AI

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