YouTube deals in the extraordinary, and shuns the ordinary. Whether that’s the everyday life of improbably rich young millionaires like Jake Paul, a high school dropout from Westlake, Ohio, or PewDiePie, a skinny, fast-talking Swede whose real name is Felix Arvid Ulf Kjellberg, YouTube seeks to serve a need.

It does so through “the algorithm” — YouTube’s recommendation engine. It’s a black box that YouTube introduced to keep us watching, but which has become a thorn in its side as the platform grows at an astronomically grand scale.

YouTube’s recommendation algorithm is a set of rules followed by cold, hard computer logic. It was designed by human engineers, but is then programmed into and run automatically by computers, which return recommendations, telling viewers which videos they should watch. Google Brain, an artificial intelligence research team within the company, powers those recommendations, and bases them on user’s prior viewing. The system is highly intelligent, accounting for variations in the way people watch their videos.

Like many aspects of Google, it is also notoriously opaque. Occasionally, however, the curtain is lifted a little. In 2016, a paper by three Google employees revealed the deep neural networks behind YouTube’s recommended videos, which rifle through every video we’ve previously watched. The algorithm then uses that information to select a few hundred videos we might like to view from the billions on the site, which are then winnowed down to dozens, which are then presented on our screens.