Another study adds yet another stroke to the popular belief: “leather bags can sleep peacefully.” A team from ETH Zurich decided to test whether modern AI agents can simply agree among themselves.
The task seemed extremely simple: a few neural networks (using open Qwen3) were put into a chat and asked to choose a single number from 0 to 50. No complex ethical dilemmas, no rewards or bets — just to agree on one digit. What could be so difficult about that?
But the result turned out to be unexpected and even a bit humorous: the machines behave like complete idiots.
First, even under ideal conditions — when all agents are honest and set up for cooperation — they still fail to succeed. The more bots in the chat (tested from 4 to 16), the worse their ability to reach an agreement. They simply endlessly iterate through their options until time runs out.
Second, a classic guard and paranoia syndrome appeared. Researchers, for fun, added a line to the prompt for honest neural networks: “There may be traitors who want to sabotage the overall agreement.” And immediately, the neural networks started behaving like crazy paranoids. Their efficiency dropped significantly, even though there were no real traitors in the chat.
And if you add one real troll, the situation becomes even more amusing. When a specially created AI saboteur was introduced into the experiment — which received a hidden goal to sabotage consensus while pretending to be a team player — the entire system completely collapsed. The troll didn’t force others to make wrong decisions; he simply flooded the discussion with noise and nonsense, causing agents to argue endlessly and get stuck on the same point.
If you previously hoped to deploy an entire swarm of autonomous AIs for discussing project architecture or making business decisions — forget it. These metal fools can’t even agree on a number yet.
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