Online Archive of University of Virginia Scholarship
Model Evaluation Service: Improving Machine Learning Model Development Efficiency / The Struggle over Digital Privacy in the United States181 views
Author
Kwong, Alex, School of Engineering and Applied Science, University of Virginia0009-0003-9603-1580
Advisors
Vrugtman, Rosanne, EN-Comp Science Dept, University of Virginia
Abstract
How can machine learning improve productivity in organizations? Recent developments
in machine learning (ML) offer new possibilities in automation that may transform numerous
economic sectors and boost organizational efficiency. Yet ML also threatens to accelerate
problematic trends, including invasion of personal privacy, unimpeded user data collection and
monetization, and propagation of targeted misinformation.
Degree
BS (Bachelor of Science)
Keywords
machine learning; data privacy; big data; digital privacy
Kwong, Alex. Model Evaluation Service: Improving Machine Learning Model Development Efficiency / The Struggle over Digital Privacy in the United States. University of Virginia, School of Engineering and Applied Science, BS (Bachelor of Science), 2023-06-07, https://doi.org/10.18130/zbm6-7a74.
