#286: How Algorithms Can Fight Extremism

Tech Policy Podcast

TechFreedom

Technology

4.8 • 45 Ratings

🗓️ 8 March 2021

⏱️ 33 minutes

🔗️ Recording | iTunes | RSS

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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.

Transcript

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0:00.0	Welcome to the Tech Policy Podcast.
0:09.2	I'm Corbyn Barthold, Internet Policy Council at Tech Freedom.
0:14.9	My guest today is Dr. Anna Zytezev.
0:17.7	She is a postdoctoral scholar at the UC Berkeley School of Information, where she focuses on software
0:23.6	design and development, social media, and algorithms. Her work has been published in leading
0:29.4	academic journals, such as information and organization, and it's been discussed in numerous
0:35.3	mainstream outlets, including CNBC and the New York Times.
0:39.6	Our discussion today will focus on her paper, Algorithmic Extremism, examining YouTube's rabbit hole of radicalization, which made quite a splash.
0:50.2	She co-authored that paper with Mark Ledwitch.
0:53.7	Doctor, it's so great to have you.
0:55.7	So glad to be here.
0:57.1	So before we dive in, I'd like to mention how I came across your work.
1:01.9	There's a little bit of a story behind it.
1:04.3	There's a legislative proposal in Florida being promoted by Governor DeSantis.
1:09.7	They're going to call it the Transparency in Technology Act.
1:13.6	As of recording, the bill itself is not out yet, but we're told that it would limit social media sites' ability to algorithmically rank content.
1:22.6	It would also limit when such sites can change their terms of service, and it would let users
1:28.0	sue if they don't think a site is applying its terms consistently.
1:33.1	As I was thinking about these proposals, I recalled a great article in Wired.
1:37.7	I recommend our listeners check it out.
1:39.8	It was issued last September.
1:42.0	It's by Clive Thompson.
	...

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