Filterworld: How Algorithms Flattened Culture

by Kyle Chayka

If recommendations are to be regulated, certain decisions have to be made based on content. “Which preferences are unacceptable and must be overridden by law?” Keller asked. “Say platforms stop giving people what they want; you have to give them something else instead. What are the veggies, what information are we forcing into the diet, and how do we decide what that is? I don’t know what the answer is,” Keller said. She has suggested a system of “circuit breakers” that are “content neutral.” Rather than deciding which content is positive or negative, any kind of content that goes viral—accelerating quickly via recommendations—would be limited instead of promoted more, slowing down its spread and giving moderators more time to judge if it’s appropriate before it reaches massive audiences. Circuit breakers could also bring us back to a less globalized media ecosystem, when pieces of content stayed more firmly within their original contexts. While this might limit innocuous content like funny videos, it also means that Russell might not have been exposed to many of the memes that harmed her. She wouldn’t have gotten that email of Pinterest “Depression Pins” urging her deeper down the rabbit hole. Decisions about content ultimately have to be made by humans, both because machine-learning systems are not yet capable of making such subtle distinctions and because their consequences impact human lives. That human capacity is not scalable in the way that software is—one person ca...