
Sign up to save your podcasts
Or


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, filter bubbles, multilingual news recommendation, and her open-source NewsRecLib framework for evaluating recommender systems. They explore why bigger models aren't always better and how future recommendation systems can balance personalization with diversity and societal impact.
By Kyle Polich4.4
475475 ratings
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, filter bubbles, multilingual news recommendation, and her open-source NewsRecLib framework for evaluating recommender systems. They explore why bigger models aren't always better and how future recommendation systems can balance personalization with diversity and societal impact.

32,100 Listeners

30,666 Listeners

289 Listeners

1,093 Listeners

626 Listeners

583 Listeners

301 Listeners

345 Listeners

208 Listeners

202 Listeners

314 Listeners

99 Listeners

576 Listeners

101 Listeners

226 Listeners