Tech Policy Podcast

#286: How Algorithms Can Fight Extremism

Episode Summary

What can social-media platforms do to address growing concerns about extremism on their sites? Research suggests that YouTube, for one, has made great strides in driving viewers of radical messages toward more mainstream content. As new forms of misinformation arise, YouTube has succeeded in quickly adjusting its algorithmic recommendations. Dr. Anna Zaitsev is a postdoctoral scholar at the UC Berkeley School of Information, and the co-author of the paper “Algorithmic extremism: Examining YouTube’s rabbit hole of radicalization.” She joins the show to discuss her research on YouTube’s recommendation system, and what it takes to spot, block, and demote ever-evolving extremist content.

Episode Notes

What can social-media platforms do to address growing concerns about extremism on their sites? Research suggests that YouTube, for one, has made great strides in driving viewers of radical messages toward more mainstream content. As new forms of misinformation arise, YouTube has succeeded in quickly adjusting its algorithmic recommendations. Dr. Anna Zaitsev is a postdoctoral scholar at the UC Berkeley School of Information, and the co-author of the paper “Algorithmic extremism: Examining YouTube’s rabbit hole of radicalization.” She joins the show to discuss her research on YouTube’s recommendation system, and what it takes to spot, block, and demote ever-evolving extremist content.