Note: This is something I originally wrote for the daily newsletter at the Columbia Journalism Review, where I’m the chief digital writer
For many people, YouTube is a place to kill time by watching sailing videos, or to pick up tips on how to train their dog, or change a car headlight. But the Google-owned video service also has a darker side, according to a number of news articles, including one from the New York Times last year. Some users, these stories say, start out looking at innocuous videos, but get pushed in the direction of more and more radical, inflammatory or even outright fake content. Those pushes come from YouTube’s recommendation algorithm, which some argue has turned the service into a “radicalization engine.” Does the network and the software that powers its video suggestions actually turn otherwise normal users into consumers of far-right conspiracy theories and other radical content, and if so what should be done about it?
Those are some of the questions we at CJR wanted to address, so we used our Galley discussion platform to convene a virtual panel of experts in what some call “automated propaganda,” including Dipayan Ghosh of Harvard’s Shorenstein Center, New York Times columnist Kevin Roose — who wrote last year’s Times piece on YouTube radicalization — as well as Brazilian researcher Virgilio Almeida, Aviv Ovadya of the Thoughtful Technology Project, former YouTube programmer Guillaume Chaslot, and Harvard misinformation researcher Joan Donovan. One trigger for this discussion was a research paper published recently that not only said YouTube is not a radicalization engine, but argued that its software actually accomplishes the opposite, by suggesting videos that push users in the direction of mainstream content. As part of our virtual Galley panel, we spoke to a co-author of that paper, Mark Ledwich.
In Twitter posts and on Medium, Ledwich took direct aim at the New York Times and Roose for perpetuating what he called the myth of YouTube algorithmic radicalization. In reality, he said, this theory showed that “old media titans, presenting themselves as non-partisan and authoritative, are in fact trapped in echo chambers of their own creation, and are no more incentivized to report the truth than YouTube grifters.” One of the main criticisms of the paper — which came from others in the field such as Arvind Narayanan of Princeton — was that the research was based on anonymized data, meaning none of the recommendations were personalized, the way they were in the New York Times piece (which used personal account data provided by the subject of the story). In his Galley interview, Ledwich pointed out that much of the research that others have used to support the radicalization theory is also based on anonymized data, in part because personalized data is so difficult to come by.
Continue reading “The YouTube “radicalization engine” debate continues”










