YouTube, the Great Radicalizer

["Dave Farber" <farber () gmail com>]

Begin forwarded message:

> From: Dewayne Hendricks <dewayne () warpspeed com>
> Date: March 11, 2018 at 11:49:50 AM EDT
> To: Multiple recipients of Dewayne-Net <dewayne-net () warpspeed com>
> Subject: [Dewayne-Net] YouTube, the Great Radicalizer
> Reply-To: dewayne-net () warpspeed com
>
> [Note:  This item comes from friend David Rosenthal.  DLH]
>
> YouTube, the Great Radicalizer
> By Zeynep Tufekci
> Mar 10 2018
> <https://www.nytimes.com/2018/03/10/opinion/sunday/youtube-politics-radical.html>
>
> At one point during the 2016 presidential election campaign, I watched a bunch of videos of Donald Trump rallies on 
> YouTube. I was writing an article about his appeal to his voter base and wanted to confirm a few quotations.
>
> Soon I noticed something peculiar. YouTube started to recommend and “autoplay” videos for me that featured white 
> supremacist rants, Holocaust denials and other disturbing content.
>
> Since I was not in the habit of watching extreme right-wing fare on YouTube, I was curious whether this was an 
> exclusively right-wing phenomenon. So I created another YouTube account and started watching videos of Hillary 
> Clinton and Bernie Sanders, letting YouTube’s recommender algorithm take me wherever it would.
>
> Before long, I was being directed to videos of a leftish conspiratorial cast, including arguments about the existence 
> of secret government agencies and allegations that the United States government was behind the attacks of Sept. 11. 
> As with the Trump videos, YouTube was recommending content that was more and more extreme than the mainstream 
> political fare I had started with.
>
> Intrigued, I experimented with nonpolitical topics. The same basic pattern emerged. Videos about vegetarianism led to 
> videos about veganism. Videos about jogging led to videos about running ultramarathons.
>
> It seems as if you are never “hard core” enough for YouTube’s recommendation algorithm. It promotes, recommends and 
> disseminates videos in a manner that appears to constantly up the stakes. Given its billion or so users, YouTube may 
> be one of the most powerful radicalizing instruments of the 21st century.
>
> This is not because a cabal of YouTube engineers is plotting to drive the world off a cliff. A more likely 
> explanation has to do with the nexus of artificial intelligence and Google’s business model. (YouTube is owned by 
> Google.) For all its lofty rhetoric, Google is an advertising broker, selling our attention to companies that will 
> pay for it. The longer people stay on YouTube, the more money Google makes.
>
> What keeps people glued to YouTube? Its algorithm seems to have concluded that people are drawn to content that is 
> more extreme than what they started with — or to incendiary content in general.
>
> Is this suspicion correct? Good data is hard to come by; Google is loath to share information with independent 
> researchers. But we now have the first inklings of confirmation, thanks in part to a former Google engineer named 
> Guillaume Chaslot.
>
> Mr. Chaslot worked on the recommender algorithm while at YouTube. He grew alarmed at the tactics used to increase the 
> time people spent on the site. Google fired him in 2013, citing his job performance. He maintains the real reason was 
> that he pushed too hard for changes in how the company handles such issues.
>
> The Wall Street Journal conducted an investigation of YouTube content with the help of Mr. Chaslot. It found that 
> YouTube often “fed far-right or far-left videos to users who watched relatively mainstream news sources,” and that 
> such extremist tendencies were evident with a wide variety of material. If you searched for information on the flu 
> vaccine, you were recommended anti-vaccination conspiracy videos.
>
> It is also possible that YouTube’s recommender algorithm has a bias toward inflammatory content. In the run-up to the 
> 2016 election, Mr. Chaslot created a program to keep track of YouTube’s most recommended videos as well as its 
> patterns of recommendations. He discovered that whether you started with a pro-Clinton or pro-Trump video on YouTube, 
> you were many times more likely to end up with a pro-Trump video recommended.
>
> [snip]
>
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