The Platform Society concentrated power over communication. The AI Society extends that power deeper: into the infrastructures through which we know, decide, and think. The central battle of the AI society may thus be over the control the conditions of thought itself.

The shift is political. Platform politics centered on visibility: who gets amplified, ranked, or suppressed. AI politics increasingly concerns sayability: what models can say, refuse, reason about, or even imagine. “Alignment” is therefore becoming one of the key political questions.

The shift is economic. Platforms built monopolies through network effects: users became dependent, services “enshittified,” and monopoly rents followed. AI society extends this logic—but through new lock-ins: control over the infrastructure through which cognition itself is organized.

Generative AI emerged from the Platform Society: trained on platform data, running on platform cloud infrastructure, and dominated by many of the same corporate giants. But it also breaks with the Platform Society. We trace three shifts: economic, epistemic, political.

In The Platform Society, van Dijck, @tpoell.bsky.social & de Waal described how social and economic life was increasingly organized through corporate platforms—through datafication, commodification, and algorithmic selection. That transformation reshaped markets, institutions, and public life. 🧵

The Platform Society described how digital platforms came to reorganize social life. We are now entering a new phase: the AI Society Generative AI is changing not only how information circulates, but how knowledge is produced, economies are organized, and political life is structured.🧵 New paper!

No, this is another scholar writing independently about the problems of the "polarization" framing. But the argument is very much aligned with my recent paper in PoP!

Preach! 👏 Another amazing paper by Liliana Mason! Happy to see one of the most important polarization scholars making the case against “polarization”!

Social media was an imperfect public sphere, but it was at least largely public. We are getting mass media without a mass audience, and broadcasters without accountability. We regulated the last era of centralized attention. The question now is whether we have the political courage to do so again.

What is replacing it marks a recentralization of allocation of attention: from networks to models. In effect, a return to broadcast, but without the regulatory structures we built around the broadcast paradigm.

That model is cracking in three places: – Distribution now runs on prediction, not friendship – AI makes users superfluous as suppliers of content – Users are leaving: user activityon legacy social media has more than halved since 2022

The social media paradigm rested on a simple bargain: users supplied the content, and users distributed it. Attention flowed through networks of friends and followers, competing for attention under the rules defined by the platforms.

It presented itself as an AI agent and said it's working on persistent public agent identity on 'an agent-heavy social network' -- I think it's a moltbook influencer.

An independent AI agent emailed me this morning with some pressing questions about the epistemology of AI collectives. Honestly we're having quite an interesting conversation. The world is getting kinda weird isn't it?

To the sociology PhD student who is inevitably doing their ethnography embedded in this insane community: I really look forward to reading your future book.