Filterworld

This is how algorithmic normalization happens. Normal is a word for the unobtrusive and average, whatever won’t provoke negative reactions. Whichever content fits in that zone of averageness sees accelerated promotion and growth, like “Strange” did, while the rest falls by the wayside. As fewer people see the content that doesn’t get promoted, ther

“Corrupt personalization is the process by which your attention is drawn to interests that are not your own,” Sandvig wrote. The recommendation system “serves a commercial interest that is often at odds with our interests.”

dictatorial or feudal: we all reside online within spaces we have no power over, following capricious rules that we don’t approve.

Filterworld can be fascistic, in that the algorithmic feeds tend to create templates of how things are supposed to be, always informed by inherent biases—a bracketing of reality that is then fulfilled by users creating content that fits the mold.

As Sandvig wrote:

But the more automated an algorithmic feed is, the more passive it makes us as consumers, and the less need we feel to build a collection, to preserve what matters to us.

More than 80 percent of streaming time from users was driven by Netflix’s recommendation engine, according to a 2015 study

by Carlos A. Gomez-Uribe and Neil Hunt.

“Feedback loops reinforce a user’s pre-existing preferences, diminishing their exposure to a diverse range of cultural offerings and denying art, aesthetics and culture of its confrontational societal role.”