16 citations · 30 across the 5 of their papers we have counts for
5 papers
Examining risks of racial biases in NLP tools for child protective services
Anjalie Field, Amanda Coston, Nupoor Gandhi +4
Although much literature has established the presence of demographic bias in natural language processing (NLP) models, most work relies on curated bias metrics that may not be refl…
Recentering Validity Considerations through Early-Stage Deliberations Around AI and Policy Design
Anna Kawakami, Amanda Coston, Haiyi Zhu +2
AI-based decision-making tools are rapidly spreading across a range of real-world, complex domains like healthcare, criminal justice, and child welfare. A growing body of research…
Counterfactual Prediction Under Outcome Measurement Error
Luke Guerdan, Amanda Coston, Kenneth Holstein +1
Across domains such as medicine, employment, and criminal justice, predictive models often target labels that imperfectly reflect the outcomes of interest to experts and policymake…
Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making
Luke Guerdan, Amanda Coston, Zhiwei Steven Wu +1
A growing literature on human-AI decision-making investigates strategies for combining human judgment with statistical models to improve decision-making. Research in this area ofte…
The role of the geometric mean in case-control studies
Amanda Coston, Edward H. Kennedy
Historically used in settings where the outcome is rare or data collection is expensive, outcome-dependent sampling is relevant to many modern settings where data is readily availa…