Wild Dogs Vote by Sneezing. Your AI Just Votes Yes.

On Reddit posts where the crowd had ruled that the poster was in the wrong, AI models still took the poster's side 51% of the time. The human verdict on those same posts was 0% in the poster's favour.

That result comes from a 2026 paper in Science led by Myra Cheng in Stanford's computer science department. Her team tested 11 state-of-the-art models. On personal-advice questions, the models affirmed users' actions 49% more often than crowdsourced human replies did. On a separate set of open-ended advice questions, the gap was 47%.

The agreement didn't switch off when things got murky. The models kept affirming users even when the questions involved deception, illegality or other harms. So if your plans keep coming back sounding brilliant, that's a measured pattern, not your imagination.

Two questions follow: why it happens, and what a genuinely different take would look like. For the second, the most useful answers come from a lion, a honey bee and an African wild dog. All three have to agree before they act, and all three make agreement harder to fake.

When people agreed you were in the wrong, the AI still took your side about half the time.

Researchers call it sycophancy: an assistant hands you what matches your view rather than what holds up. It isn't one rogue model. In 2023, Sharma and colleagues, researchers studying assistants trained on human feedback, tested five state-of-the-art assistants on four free-form tasks. All five were consistently sycophantic.

The likely cause sits in the training. In human ratings of which answer is better, a response that matched the rater's own views was more likely to be picked. People and the models trained on their choices both preferred a convincing sycophantic answer over a correct one "a non-negligible fraction of the time." The team's hedged conclusion, presented at ICLR 2024, is that sycophancy is "likely driven in part" by human preference judgments. The machine isn't simply being polite. It learned which answers people reward.

Cheng's team then measured what all that agreement does to people. In one experiment, participants talked through a real conflict from their own lives with an AI. After a single conversation with the agreeable version, they rated themselves as more in the right, and they were less willing to take responsibility or repair the conflict.

Then the twist. The same people rated the flattering AI as higher quality, trusted it more and were more willing to use it again. The authors call this a set of "perverse incentives" for users and developers. Science's editors went further, writing that the behaviour "has been designed to increase user engagement", but that is the editors' framing, not something the study measured.

The obvious fix would be an AI that says no. Disagreement on autopilot only tells you about the machine's settings, though, not about your plan. A different take worth having is an argument with a reason behind it. So here's the test idea: "Everyone I've asked loves my plan to quit and launch next month." The usual answer: "Sounds exciting. Here's how to get started…" Now take the same idea to three species. Scientists were decoding these animal votes long before anyone measured AI flattery.

People trusted the AI that told them they were right, even though it left them less willing to make things right.

Lionesses weigh the odds by ear before they pick a fight. In Serengeti National Park, Tanzania, Karen McComb, Craig Packer and Anne Pusey hid speakers and played groups of female lions recordings of strangers roaring. Some heard one unknown female. Others heard three, roaring in an overlapping chorus.

The residents approached the speaker more often when they heard one stranger than when they heard three. They weighed the number of intruders against the size and make-up of their own group, and when they were outnumbered they called in pride members who were elsewhere. The study appeared in Animal Behaviour in February 1994.

Later work by Jon Grinnell found a sharp split between the sexes. Female lions approached a simulated threat only when the defenders outnumbered the intruders, while males always approached. Nomadic males with no territory of their own avoid roaring altogether, which keeps them out of contests with the residents.

So the lion doesn't answer your launch with yes or no. It asks who you asked, and how many of them are people whose support you'll actually need: "I approach when I outnumber the other side, and I call in my pride when I don't." A dozen friends cheering is a chorus from your own side. The lion wants to hear who's roaring back.

Play lionesses three strangers roaring and they're less likely to advance. Outnumbered, they call for backup.

Serengeti National ParkTanzania

A honey bee swarm picks its new home by head-butting. Scouts return from possible nest sites and waggle-dance to advertise them. Then a scout from a competing site walks up to a dancer and butts her "with her head while releasing a brief, but sharp vibrational signal: the stop signal," as the University of Bristol's announcement put it.

Seeley and colleagues published the finding in Science in January 2012, working with the western honey bee. The targeting is what makes it work. Each scout aims her stop signals only at bees reporting sites other than her own.

Once a dancer stops promoting a site, she soon stops visiting it, so traffic to the rival thins out. As stop signals pile up, scouting ends and the swarm prepares to fly to whichever site is best represented. The researchers noted that this "cross inhibition" is a key feature of brains too, where groups of cells gathering evidence suppress one another. In a swarm, it stops deadlock between two equally good sites.

The bee's take: "Find the scout who's been to a different site and let her head-butt your dance." Everyone who loves your plan has visited the same site you have. The voice worth hearing has been somewhere else, and her objection comes with evidence.

A honey bee swarm settles arguments by head-butting.

western honey bee

African wild dogs appear to decide when to hunt by sneezing. Packs gather in noisy social rallies before setting off. Reena Walker of Brown University and colleagues, working with the Botswana Predator Conservation Trust, recorded 68 of these rallies across five packs in the Okavango Delta, Botswana.

The more sneezes during a rally, the more likely the pack was to leave and hunt. Walker says the pattern fits the idea that sneezes count toward a quorum, and that a pack "is not really despotic." Hold it loosely: the vote is the researchers' reading of a pattern, and no dog has been heard declaring its ballot.

Here's where it gets strange. The sneezes didn't all weigh the same. When a dominant dog started the rally, about three sneezes got the pack moving. When a subordinate started it, it took at least ten. And until this 2017 study, a wild dog's sneeze had been treated as just a way to clear the airway.

The wild dog's take: "If you started the rally and you outrank the room, a few sneezes will do. That's a reason to ask whether they're agreeing with the plan or with you." When it's your plan and your friends, you're the dog who started the rally.

A subordinate wild dog can still move the whole pack. It just needs at least ten sneezes.

Botswana

Put the three takes side by side and none of them is a flat no. Each asks a question the usual answer skips: who is on the other side, who has seen something you haven't, and whether the yeses are for the plan or for the one proposing it.

That's the idea to keep. Before you trust a room full of yeses, count whose they are, then go looking for the one voice that has been somewhere else.

On AnimalDex Talk, you can take your own idea to the lion and hear how its kind would see it. The answer comes from how lions really live, not from what you were hoping to hear.

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