This quote raises questions: "The scraped data, as well as the YouTube API, provides usa view of the recommendations presented to an anonymous account. In other words, the account has not ”watched” any videos, retaining the neutral baseline recommendations, described in further detail by YouTube in their recent paper that explains the inner workings of the recommendation algorithm[38]. One should note that the recommendations list provided to a user who has an account and who is logged into YouTube might differ from the list presented to this anonymous account."

Many discussions of radicalization talk about recommendations coming after someone has watched a number of videos.

This situation is that after N videos, the algorithm starts to see a pattern, a niche, that the user fits into and then recommends more niche content. Once the user watches the niche content, just more niche content is recommended, or that-niche and mainstream content is recommended and the mainstream content is boring.

In a sense, I don't see how a blind recommendation system could escape this situation. It seems more an inherent problem of blind recommendation systems.

What could be a better approach?

* Better education in the US and the world so people have BS detectors?

* Instead of unlabeled recommendations, the algorithm categorizes what you're seen, categorizes what it's recommending and let's the user say what category they want and remove or add categories for recommendation.

* Have more ordinary search tool and a better categorization system (Youtube is a horrible black-box now, search is terrible, recommendations is terrible, I get videos from other sites mostly).