Can randomness organize itself into structure?
Benedict Evans recently framed the puzzle this way in a LinkedIn post:
“If we make probabilistic systems big and complicated enough they might become deterministic. But if we make deterministic systems big and complicated enough then they become probabilistic.”
In other words, scale blurs the line between order and randomness. Yet most conversations focus on computational scale—bigger models, more data. What happens when probabilistic systems scale socially instead?
Emergence in the Wild
A new peer-reviewed study from City St George’s and the IT University of Copenhagen offers a clue. Researchers paired language-model agents at random and asked each pair to agree on a label for an object. No global memory, no overseer. Still, the agents converged on a single shared label—and a tiny minority could later tip the entire group toward a new one. Local noise produced global order.
A Quick Micro-Experiment
We reenacted the idea with ten toy agents arguing over the best single life hack. Each round they debated in pairs, could forget older debates (memory decay), and sometimes switched to a more persuasive idea.
| Round | Followers of 25-min focus timer |
|---|---|
| 1 | 0 |
| 2 | 4 |
| 3 | 8 |
Within three rounds, the 25-minute focus timer swept the room as the best single life hack — not because it was objectively superior, but because its clarity and catchiness made it easy to spread. Probabilistic agents, interacting, produced an outcome that felt deterministic.
Why It Matters
The experiment hints that structure can emerge from interaction, not just computation. Maybe the needle of AI progress doesn’t always move upward; maybe it spreads sideways, through social alignment.
And for projects like Rejuve.AI — where thousands of people (and eventually agents) will contribute data and insights — understanding social-scaling intelligence could be the next unlock in collaborative health research.
