YouTube’s Deradicalization Argument Is Really a Fight About Transparency
The reason we’re all focusing on the algorithm’s effects is we don’t know how it really works
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YouTube’s algorithm has once again been thrust into the limelight as 2019 comes to an end, with a new study published on the arXiv, an academic repository for what are commonly referred to in academia as “pre-print” papers (which haven’t been peer-reviewed) about the code that makes the platform tick.
The paper, authored by programmer Mark Ledwich and a UC Berkeley researcher, Anna Zaitsev, looks at the role YouTube’s algorithm plays in recommending videos to users. Outside the paper, Ledwich has gone further, saying his data — which shows that YouTube’s algorithm is recommending videos from mainstream publishers — demonstrates, contrary to many media headlines, that YouTube’s algorithm “deradicalizes” users.
His co-author, Zaitsev, distanced herself from Ledwich’s comments when approached by FFWD. “ We don’t really claim that it does deradicalize, we rather say that it is a leap to say that it does,” she says. “The last few comments about deradicalization are blown out of proportion on Twitter. Our main point is rather in the direction of the traffic.”
When asked if she disagreed with Ledwich’s claim that “the algo has a deradicalizing influence”, Zaitsev says: “My contribution is within the paper, not the Medium posts or Twitter.”
The paper has been submitted to open-access journal First Monday for peer-review, where the rigor of the research will be checked. If sufficient, the paper will be accepted for publication.
Ledwich’s suggestion that the YouTube algorithm deradicalizes users is a leap in a number of ways, not least because showing people videos from mainstream channels doesn’t mean you’re deradicalizing them at all. Arvind Narayanan, a Princeton computer science professor, has debunked the claims made in a Twitter thread here, as have a number of journalists including myself, pointing out that Ledwich has tracked YouTube’s algorithm at the tail end of a change instigated by the platform after negative headlines about the potential of the algorithm to spool people off into dangerous niches.
