Disentanglement and Interpretability in Recommender Systems

Recommender systems influence nearly every aspect of our digital lives—but what does it mean for those systems to be fair? Robin Burke joins Data Skeptic to discuss the history of recommender systems,...

27 Jul 42min

News recommendation algorithms influence far more than what stories we click—they can shape our understanding of the world. In this episode, Kyle Polich speaks with Andreea Iana about responsible AI, ...

2 Jul 46min

What if you could simply tell a recommendation system what you want instead of relying on likes, dislikes, and watch history? Kyle Polich talks with Fuyuan Lyu about the DPR framework, which combines ...

23 Jun 35min

How can researchers audit recommendation systems when the algorithms are hidden from view? Hieu Le joins Kyle Polich to discuss Auto-Like, a reinforcement learning framework that systematically explor...

17 Jun 35min

Aaron Payne, an MBA student at Georgia Tech studying business analytics and a Senior Insights Analyst at Chick-fil-A, joins Kyle Polich to talk about turning analytics into decisions that matter. They...

1 Mai 25min

Kyle Polich sits down with Yashar Deldjoo, research scientist and Associate Professor at the Polytechnic University of Bari, to explore how recommender systems have evolved and why trustworthiness mat...

25 Apr 49min

Goodreads star ratings can be misleading as measures of "book quality," and research from Hannes Rosenbusch suggests that for many professionally published books, differences between readers often mat...

27 Mar 39min