Artificial-Intelligence

How Facebook went all in on AI

How Facebook went all in on AI | itkovian

The listed authors were “Zuckerberg et al.” and the product was the News Feed.

The idea of showing users streams of activity wasn’t entirely new—­ photo-­sharing website Flickr and others had been experimenting with it—­ but the change was massive. Before, Facebook users would interact with the site mainly via notifications, pokes, or looking up friends’ profiles. With the launch of the News Feed, users got a constantly updating stream of posts and status changes. The shift came as a shock to what were Facebook’s then 10 million users, who did not appreciate their activities being monitored and their once-­ static profiles mined for updated content. In the face of widespread complaints, Zuckerberg wrote a post reassuring users, “Nothing you do is being broadcast; rather, it is being shared with people who care about what you do—­ your friends.” He titled it: “Calm down. Breathe. We hear you.”

Hearing user complaints wasn’t the same thing as listening to them. As Chris Cox would later note at a press event, News Feed was an instant success at boosting activity on the platform and connecting users. Engagement quickly doubled, and within two weeks of launch more than a million members had affiliated themselves with a single interest for the first time. The cause that had united so many people? A petition to eradicate the “stalkeresque” News Feed.

The opaque system that users revolted against was, in hindsight, remarkably simple. Content mostly appeared in reverse chronological order, with manual adjustments made to ensure that people saw both popular posts and a range of material. “In the beginning, News Feed ranking was turning knobs,” Cox said.

Fiddling with dials worked well enough for a little while, but everyone’s friend lists were growing and Facebook was introducing new features such as ads, pages, and interest groups. As entertainment, memes, and commerce began to compete with posts from friends in News Feed, Facebook needed to ensure that a user who had just logged on would see their best friend’s engagement photos ahead of a cooking page’s popular enchilada recipe.

The first effort at sorting, eventually branded “EdgeRank,” was a simple formula that prioritized content according to three principal factors: a post’s age, the amount of engagement it got, and the interconnection between user and poster. As an algorithm, it wasn’t much—­ just a rough attempt to translate the questions “Is it new, popular, or from someone you care about?” into math. 

There was no dark magic at play, but users again revolted against the idea of Facebook putting its thumb on what they saw. And, again, Facebook usage metrics jumped across the board.

The platform’s recommendation systems were still in their infancy, but the dissonance between users’ vocal disapproval and avid usage led to an inescapable conclusion inside the company: regular people’s opinions about Facebook’s mechanics were best ignored. Users screamed “stop,” Facebook kept going, and everything would work out dandy.

Hi, I’m Samuel