Brands and bots cannot access Spread and, like PI.FYI, the platform does not support ads. Instead of working to maximize time on site, Rogers’ primary success metrics will be indicators of “meaningful” human engagement, such as when someone clicks on another user’s recommendation and then takes action like subscribing to a newsletter or a subscription. He hopes this will align companies whose content is shared on Spread with the platform’s users. “I think there’s a nostalgia for what the original social media was intended to achieve,” Rogers says.
So you joined a social network without ranking algorithms. Is everything okay now? Jonathan Stray, senior scientist at UC Berkeley’s Center for Human-Compatible AI, has doubts. “There is now a lot of research showing that chronological is not necessarily better,” he says, adding that simpler feeds can promote recency bias and enable spam.
Stray does not believe that social harm is an inevitable result of complex algorithmic healing. But he agrees with Rogers that the tech industry’s practice of trying to maximize engagement doesn’t necessarily select for socially desirable outcomes.
Stray suspects that the solution to the problem of social media algorithms may, in fact, be… more algorithms. “The fundamental problem is that there is too much information for anyone to consume, so you have to reduce it somehow,” she says.
In January, Stray released the Prosocial Sorting Challenge, a competition with a $60,000 prize pool that aims to spur the development of feed ranking algorithms that prioritize socially desirable outcomes, based on measures of users’ well-being and how informative a feed is. From June to October, five winning algorithms will be tested on Facebook, X, and Reddit using a browser extension.
Until a viable replacement takes off, escaping engagement-seeking algorithms will usually mean going chronological. There is evidence that people are looking for this beyond specialist platforms like PI.FYI and Spread.
Group messages, for example, are commonly used to complement artificially curated social media feeds. Private chats, connected by clock logic, can provide a more intimate and less chaotic space for sharing and discussing information from the algorithmic realm: the exchange of jokes, memes, links to videos and articles, and screenshots of social posts.
Disdain for the algorithm could help explain the growing popularity of WhatsApp in the United States, which has long been ubiquitous elsewhere. Messaging app Meta saw a 9 percent increase in daily users in the US last year, according to Apptopia data reported by The envelope. Even within the dominant social applications today, activity is shifting from public sources to direct messagingaccording Business Insiderwhere chronology rules.
Group chats may be ad-free and relatively controlled social environments, but they come with their own biases. “If you look at sociology, we’ve seen a lot of research showing that people naturally look for things that don’t cause cognitive dissonance,” says Drake University’s Stoldt.
While providing a more organic means of compilation, group messages can still produce echo chambers and other errors associated with complex algorithms. And when the content of your group chat comes from each member’s highly personalized algorithmic feed, things can get even more complicated. Despite the flight to spaces free of algorithms, the fight for a perfect source of information is far from over.