2 citations · 2 across the 1 of their papers we have counts for
4 papers
Characterizing Fairness Over the Set of Good Models Under Selective Labels
Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova
Algorithmic risk assessments are used to inform decisions in a wide variety of high-stakes settings. Often multiple predictive models deliver similar overall performance but differ…
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
Amanda Coston, Neel Guha, Derek Ouyang +3
Anonymized smartphone-based mobility data has been widely adopted in devising and evaluating COVID-19 response strategies such as the targeting of public health resources. Yet litt…
Counterfactual Predictions under Runtime Confounding
Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova
Algorithms are commonly used to predict outcomes under a particular decision or intervention, such as predicting whether an offender will succeed on parole if placed under minimal…
Counterfactual Risk Assessments, Evaluation, and Fairness
Amanda Coston, Alan Mishler, Edward H. Kennedy +1
Algorithmic risk assessments are increasingly used to help humans make decisions in high-stakes settings, such as medicine, criminal justice and education. In each of these cases,…