On Spread, users cannot create or upload original text or media. Instead, all posts on the platform are links to content from other services, including news articles, songs and videos. Users can adjust their timeline feeds by following other users or choosing to see more of a certain type of media.
Brands and bots are excluded from Spread and, like PI.FYI, the platform does not support advertisements. Instead of seeking to maximize time spent on site, Rogers’ primary indicators of success will be indicators of “meaningful” human engagement, such as when someone clicks on another user’s recommendation and then takes action such as signing up for a newsletter or subscribing. 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 wanted to achieve,” Rogers says.
So you joined a social network without ranking algorithms: is everything okay now? Jonathan Stray, a senior scientist at UC Berkeley’s Center for Human-Compatible AI, has his doubts. “A lot of research now shows that timeline is not necessarily better,” he says, adding that simpler feeds can promote recency bias and enable spam.
Stray doesn’t think social harm is the inevitable result of complex algorithmic curation. But he agrees with Rogers that the tech industry’s practice of maximizing engagement doesn’t necessarily select for socially desirable outcomes.
Stray suspects that the solution to the social media algorithm problem might actually be… more algorithms. “The fundamental problem is that you have way too much information for anyone to consume, so you have to reduce it somehow,” he says.
In January, Stray launched the Prosocial Ranking Challenge, a $60,000 prize competition aimed at spurring the development of feed ranking algorithms that prioritize socially desirable outcomes, based on measures of well-being users and the informative nature of a flow. 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 taking a chronological approach. There is evidence that people are looking for this beyond niche platforms like PI.FYI and Spread.
Group messaging, for example, is commonly used to supplement artificially curated social media feeds. Private chats, guided by clock logic, can provide a more intimate and less chaotic space to share and discuss gleanings from the algorithmic domain: exchanging 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. Meta’s messaging app saw a 9% increase in daily users in the United States last year, according to Apptopia data reported by The Wrap. Even within today’s dominant social apps, activity is shifting from public feeds to direct messaging, according to Business Insiderwhere chronology reigns.
Group chats can be ad-free and relatively controlled social environments, but they carry their own biases. “If you look at sociology, we’ve seen a lot of research that shows that people naturally seek out things that don’t cause cognitive dissonance,” says Drake University’s Stoldt.
While providing a more organic means of compilation, group messaging can still produce echo chambers and other pitfalls associated with complex algorithms. And when your group chat content comes from each member’s highly personalized algorithmic feed, things can get even more complicated. Despite the flight to algorithm-free spaces, the struggle for perfect information flow is far from over.
