AI's Phase Transition Noise

The Sound of a System Changing

Articles like “The AI-Powered Web Is Eating Itself” https://www.noemamag.com/the-ai-powered-web-is-eating-itself/ frame AI as a breaking point for the internet — a moment where incentives collapse, creators are erased, and the web begins consuming its own foundations. The tone is familiar: something vital is being lost, and the damage may be irreversible.

But much of what’s being described isn’t destruction. It’s noise.

Specifically, it’s phase-transition noise — the turbulence a complex system makes while reorganizing into a new equilibrium.

The pre-AI web was already brittle. Discovery was winner-take-most, SEO drowned out originality, traffic was a proxy for value rather than a measure of it, and most content was effectively invisible. AI didn’t break this system; it stripped away the friction that concealed its weaknesses. Compression replaced browsing, summaries replaced scavenger hunts, and the redundancy of the web suddenly became obvious.

From inside the transition, this feels like collapse. Interfaces change faster than institutions. Old metrics stop working. Revenue models tied to clicks unravel. That local entropy is real — some sites will vanish, some careers will shrink, some forms of writing will no longer be economically viable. But local disorder is not global decay. In complex systems, it’s often the precondition for higher-order structure.

Crucially, user intent hasn’t disappeared. People who want brief answers get them faster now. People who need depth — journalists, analysts, researchers, obsessives — can still find primary sources, often more efficiently, aided by tools that surface clusters of links, perspectives, and provenance on demand. AI doesn’t block seriousness; it lowers the cost of reaching it when it’s actually needed.

What many of these essays mourn is not the loss of knowledge, but the loss of a business model and a familiar status hierarchy. They mistake the erosion of traffic for the erosion of truth, and interface change for epistemic failure. Yet knowledge doesn’t die when it’s summarized. It dies when discovery goes unfunded — a problem that long predates AI and won’t be solved by preserving artificial friction.

Every major leap in information technology has sounded like this while it was happening. The printing press, broadcast media, the web itself — all produced a chorus of warnings about collapse that, in hindsight, were the soundtrack of emergence. Optimization always sounds destructive before new structure stabilizes.

What we’re hearing now is not the web eating itself. It’s the noise of a new information metabolism forming.