Our World Statistics Day conversations have been a great reminder of how much statistics can inform our lives. Do you have an example of how statistics has made a difference in your life? Share your story with the Community!
Choose Language Hide Translation Bar
Why we lack consensus on how to define machine learning and other terms

Dick De Veaux, Williams College, talks about the seven deadly sins of machine learning.Dick De Veaux, Williams College, talks about the seven deadly sins of machine learning.Dick De Veaux, Williams College, talks about common buzzwords, what they mean and when they are useful, in a recent livestream on machine learning and artificial intelligence. You can watch his keynote talk and follow-up panel conversation on demand. 

“Let’s talk about deep learning first. I love that term. I just wish statisticians had thought of using deep learning for linear regression. We’d have so many more followers if we were better marketers in that.

"I looked up the opposite of learning and found out there really is no opposite. It’s teach, but that’s not quite what we mean.

"So the one reference is to George Orwell’s 1984: It would be unlearning. So I guess the opposite would be shallow unlearning. And who would want that? How can we not want deep learning? It sounds great.

"What people fail to realize is what it is: a multi-layered artificial neural network that is just a big function fitter. Which works great for some things: self-driving cars, things like that. You wouldn’t want anything else. As I said, it doesn’t mean we should throw everything out and just use that.”

Here's a preview of the panel discussion, which you can watch on demand: