The latest episode of the In Context Podcast features a conversation with artificial intelligence researchers Randy Goebel and Osmar Zaiane, both professors at the Alberta Machine Intelligence Institute (AMII) at the University of Alberta. We discuss the limitations of deep supervised learning and discuss alternatives to make it easier to understand, explain, and teach machine learning systems. 

In the podcast, you’ll learn about: 

  • The difference between machine learning and data mining
  • Why it’s important to represent patterns in data at multiple levels
  • The difference between human learning and machine learning
  • What explainable AI means and doesn’t mean
  • How social values influence outcomes we optimize for
  • When reinforcement is useful and when it’s not 

About Randy and Osmar

Mentioned in the Interview