Why Are We Using Black Models in AI When We Don’t Need to? A Lesson from an Explainable AI Competition
This report from an explainable AI competition raises the question whether model developers need to rely on “black box” machine learning techniques or can meet their needs using more interpretable forms of machine learning.
Cynthia Rudin and Joanna Rudin, Harvard Data Science Review
November 1, 2019