That era seems quaint now. Our social media feeds are full of unbidden and fringe content, thanks to social media’s embrace of two key technological developments: personalization, spurred by mass collection of user data through web cookies and Big Data systems, and algorithmic amplification, the use of powerful artificial intelligence to select the content shown to users.
Personalization and algorithmic amplification, by themselves, have undoubtedly made wonderful new internet services possible. Tech users take for granted our ability to personalize apps and websites with our favorite sports teams, musicians and hobbies. The use of ranking algorithms by news websites for their user comment sections, traditional cesspools of spam, has been widely successful.
But when data scientists and software engineers blend content personalization and algorithmic amplification — as they do to produce Facebook’s News Feed, TikTok’s For You tab and YouTube’s recommendation engine — they create uncontrollable, attention-sucking beasts. Though these algorithms, such as Facebook’s “engagement-based ranking,” are marketed as increasing “relevant” content, they perpetuate biases and affect society in ways that are barely understood by their creators, much less users or regulators.
In 2007, I started working at Facebook as a data scientist, and my first assignment was to work on the algorithm used by News Feed. Facebook has had more than 15 years to demonstrate that algorithmic personal feeds can be built responsibly; if it hasn’t happened by now, it’s not going to happen. As Ms. Haugen said, it should now be humans, not computers, “facilitating who we get to hear from.”
Though understaffed teams of data scientists and product managers like Ms. Haugen attempt to keep the algorithms’ worst impacts in check, social media platforms have a fundamental economic incentive to keep users engaged. This ensures that these feeds will continue promoting the most titillating, inflammatory content, and it creates an impossible task for content moderators, who struggle to police problematic viral content in hundreds of languages, countries and political contexts.