How We Think About Privacy and Finding Features in Black Boxes

In episode eleven we chat with Neil Lawrence from the University of Sheffield. We talk about the problems of privacy in the age of machine learning, the responsibilities that come with using ML tools and making data more open. We learn about the Markov decision process (and what happens when you use it in the real world and it becomes a partially observable Markov decision process) and take a listener question about finding insights into features in the black boxes of deep learning.