4 citations · 7 across the 4 of their papers we have counts for
4 papers
A Preliminary Framework for Intersectionality in ML Pipelines
Michelle Nashla Turcios, Alicia E. Boyd, Angela D. R. Smith +1
Machine learning (ML) has become a go-to solution for improving how we use, experience, and interact with technology (and the world around us). Unfortunately, studies have repeated…
Exploring Culturally Informed AI Assistants: A Comparative Study of ChatBlackGPT and ChatGPT
Lisa Egede, Ebtesam Al Haque, Gabriella Thompson +3
In recent years, we have seen an influx in reliance on AI assistants for information seeking. Given this widespread use and the known challenges AI poses for Black users, recent ef…
What Makes An Expert? Reviewing How ML Researchers Define "Expert"
Mark Díaz, Angela DR Smith
Human experts are often engaged in the development of machine learning systems to collect and validate data, consult on algorithm development, and evaluate system performance. At t…
(Re)Defining Expertise in Machine Learning Development
Mark Díaz, Angela D. R. Smith
Domain experts are often engaged in the development of machine learning systems in a variety of ways, such as in data collection and evaluation of system performance. At the same t…