Author: Robert Wiblin, Keiran Harris, Chris Olah
Publisher: 80,000 Hours
Publication Year: 2021
Summary: The following podcast episode features Chris Olah, a researcher at Google focused on data interpretability, specifically as it relates to neural networks and big machine learning algorithms. The interview provides a deep dive into some of the issues around data interpretability and why the data “black box” issue is a problem worth solving.