Prosocial Design After Social Media
Prosocial Design Network asks their members whether prosocial design still matters.
By Audrey Hingle and Julia Kamin
In a court filing defending itself against the US Federal Trade Commission's antitrust case, Meta argued it isn't really a social media company anymore. According to numbers cited by Meta in the filing and referenced in the paper “Towards a Post-Social Media Studies”, only 7% of time on Instagram, and 17% on Facebook, goes to content from friends or accounts people follow. The overwhelming remainder goes toward watching videos recommended by AI-powered algorithms created by Meta.
To date, most prosocial design research has been done on what we used to refer to as "global town square" platforms. These were Facebook, Twitter and similar networks where people posted their own content in public, and anyone could reply to anyone. So if most of what people see in their feeds now comes from strangers or is generated by AI, and their real conversations happen in group chats or with chatbots, our field – those of us working to create and test prosocial design solutions – need to ask where our work matters most now, and how it may need to change.
On June 30, Prosocial Design Network (PDN) hosted a community conversation on that question. As pre-reading, we shared recent pieces: danah boyd on how social media became parasocial, Petter Törnberg and Richard Rogers on what's replacing social media, and New_ Public’s vision on where online public spaces will move “After the Feed.” Below we summarised key points from each of the three pieces, if you'd like to see a summary of the discussion you can find that on the PDN blog.
Background reading
Social media became parasocial media
danah boyd helped establish the term "social network sites" among academics back in 2007, so it carries weight when she argues in Social Media Is Now Parasocial Media, and that the “social” label no longer fits. In 2006, most people who logged in to social networks posted something because they were building a space to hang out with others. In 2026, posting has waned and most people scroll. What they scroll through is mostly polished content from advertisers and creators who've learned to work the algorithm. Your 15 friends might still post, but buried among polished, professionally made content, you may never see it.
The result, boyd argues, is parasocial media. One-sided relationships with people who don't know you and never reciprocate your engagement. Those relationships can be emotionally intense, but they don't build community. They don’t notice your sad Instagram post and call you up when you’re struggling, and you can feel lonely after hours of following other people's drama. She ties this incentivization structure where first, a platform attracts users with a great service. Once they're locked in, it starts abusing them to benefit business customers like advertisers. When the business customers are locked in too, it exploits both groups to appease investors. Finally, the platform dies. boyd puts most big platforms in its third stage, squeezing both users and business customers to please investors.
But people haven't stopped socializing online, they just aren’t doing it on “social media” platforms any longer. They've moved to texting and group chats, services most people don’t think of as social media. For applying prosocial design research, that could be a challenge – most of what we know about effective prosocial design in mass social media could be irrelevant, or even counter-productive, in spaces that have vastly different features and contexts.
What's replacing the feed
Petter Törnberg and Richard Rogers cover even more ground, looking beyond the big platforms to where social media as a whole is heading in Towards a Post-Social Media Studies. They name three forces pulling the old model apart, largely reflecting the trends boyd described.
The first is the algorithm. Feeds are now built around what a model predicts you'll watch based on past behavior, mostly from strangers, instead of who you follow. “TikTok’s AI-driven algorithm is often called the most addictive on social media” says Weekly Silicon Valley. It set the bar, and Instagram, Facebook, YouTube and X have all moved in that direction. The signals platforms used to determine what you’re interested in have subsequently changed. Likes and comments count for less than watch time, completion rate, rewatching and even the half-second you hesitate mid-scroll. The authors call the result "personalized broadcasting."
The second is generative AI. Generative AI models can create content just for you, and fill up your feed at almost no cost, so platforms depend less on people posting. The surreal "Shrimp Jesus" images that spread on Facebook in 2023 were early examples of this. Even though they were obviously fake, platforms had little reason to filter them out because they got so much engagement.
The third is a retreat from publicness. People are posting less in public and moving their social lives to private messaging groups and closed communities. Törnberg’s own data show posting and viewing on Facebook and X fell by nearly half between 2020 and 2024, and a growing share of people are opting out of social media entirely.
In place of social media, they see three things emerging: algorithmic broadcasting platforms like TikTok, semi-private spaces like group chats and invite-only communities, and AI chatbots, which they treat as a new kind of media. More people, they say, now talk to AI chatbots than post on social media. In 2025, 52% of US adults said they used AI chatbots, while in 2023 only 35% said they’d posted on Facebook, and 11% on X.
For researchers who wish to study these spaces, access is an issue. Platforms keep the watch-time data behind broadcast feeds to themselves, and semi-private spaces are closed by design, so the most socially meaningful conversations are the hardest to see. Chatbot conversations are even harder to study. Each one is private between a person and an AI, so there are no public posts for researchers to look at. Törnberg and Rogers suggest going back to slower, smaller methods that suit these spaces better, like ethnography, interviews, looking at how platforms are designed, and setting up test accounts to see what feeds actually show people.
Trust over reach
New_ Public's After the Feed, by Eli Pariser, Angelica Quicksey and Arnobio Morelix, focuses on the semi-private spaces Törnberg and Rogers identify. New_ Public offers an explanation for the retreat from publicness, and looks at the smaller spaces where people talk with their communities and networks once they stop posting to social media.
Their core observation is that the attention economy is giving way to a trust economy. Once followers and reviews can be faked at scale, engagement numbers stop meaning much. They cite a report from Imperva that 51% of internet traffic in 2024 was automated. That number has gone up, and the most recent report shows bots accounted for 53% of all internet traffic in 2025. When you can’t tell who’s real, open platforms stop feeling like places to talk. 58% of people in the Reuters Institute’s 2025 Digital News Report said they worried about telling real from fake online. So people take their real social lives to group chats, Discord servers, WhatsApp groups and private channels, what Maggie Appleton calls the cozy web: places where you know who you’re talking to and shared norms protect you.
LLM-based chatbots and the agents built on them are also replacing some of the reasons people talked to each other in the first place. For example, monthly questions on Stack Overflow, where developers ask questions and other developers answer, have dropped steeply since ChatGPT launched. New_ Public mapped 134 things people use social platforms for and scored how easily AI could replace each one. Learning and deciding (tutorials, quick answers) scored highest. Connecting and belonging scored lowest, which is why they rate relationship-based apps like WhatsApp and Discord as far less exposed than YouTube or TikTok to being replaced by AI chatbots and agents.
An important point from New_ Public’s deck: private spaces are good for trust and bad for bridging across differences, and democracy depends on bridging. Some of what New_ Public proposes for small spaces, like setting norms and rules, already has evidence behind it. Others, like using AI to support stewards, haven’t been tested yet. How small spaces can connect to each other when it matters is still an open question for prosocial design research.
What we know least about: agents
Across all three readings, what we know least about is how agentic AI will affect Prosocial Design. New_ Public calls AI agents the ‘new new gatekeepers’: an agent may summarize or rewrite your friends’ messages before you ever see them. Participants on our call raised specific worries, like what happens when AI-generated content is forwarded again and again through small group chats, and how easily someone could inject agent-written misinformation into a space built on trust.
Our Community Conversation
Our community conversation was open to all PDN members on our Slack workspace. (Interested in joining the next conversation? Join us on Slack.) Sixteen members showed up on June 30th, 2026 for a call on Zoom where we asked two questions and then listened. The first question was “What did the reading miss?” The second: “Looking at the future landscape of online spaces, is prosocial design research still valuable and – if so – where should it focus.” If you want to read what we discussed, we summarize what we heard on the PDN blog.
Tech for Palestine Becomes Member-Driven Organization
Tech for Palestine (T4P), whose projects have reached more than 10 million users in less than three years, has opened its membership to the public. Anyone can become a member and build advocacy projects under the T4P banner. Members get a team to work with and the backing of the organization behind Big Tech alternatives such as UpScrolled and Thaura, and advocacy tools such as Boycat and NewsCord. Members join with the skills they have: engineering, design, research, writing or organizing. Some join an existing project; others bring their own idea and start a new team, which T4P mentors help scope and staff with fellow members.
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From the Group Chat: The US Midterms 👥 💬
Last week, IX's Mallory Knodel wrote that Big Tech was betting big on the US midterms. This week, it looks like they lost the bet. At The Atlantic, Matteo Wong writes that Silicon Valley lost big. Voters in at least 10 states approved dozens of data center restrictions and backed candidates who ran against Big Tech. Brian Merchant agrees. By his count, voters moved to restrict data centers in 40 of the 41 ballot measures about them. He calls the results a defeat for data centers, AI and tech oligarchs alike. But, he warns, the industry is already courting the newly elected Democrats. Wired’s results roundup shows that voters backed candidates who support data center moratoriums at every level of government, including new Democratic governors in Georgia and Texas, which are two of the biggest hubs for data center development in the country.
Data & Society reads the night as a referendum on the tech industry. They say that voters rejected the industry’s agenda and sent the next Congress a clear message to regulate AI and hold tech companies accountable. Will this election result in new regulations? Alexandra Reeve Givens, Robert Weissman and Brian J. Chen are having a conversation about the impact of the midterm elections on US tech policy later today with Tech Policy Press.
The platforms should also be scrutinized for how they handled the election itself. This was the first US election with generative AI built into every major social media platform, from embedded chatbots and media generation tools to content moderation. Yet an Institute for Strategic Dialogue report found that companies disclosed little about how those systems work, and over the same period they cut back on human fact-checking and safety teams.
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