If you ask someone to guess the number of sweets in a jar, the odds that they’ll land upon the right number are low – fairground raffles rely on that inaccuracy. But if you ask many people to take guesses, something odd happens. Even though their individual answers can be wildly off, the average of their varied guesses tends to be surprisingly accurate.

This phenomenon goes by many names – swam intelligence, wisdom of the crowd, vox populi, and more. Whatever it’s called, the principle is the same: a group of people can often arrive at more accurate answers and better decisions than individuals acting alone. There are many examples, from counting beans in a jar, to guessing the weight of an ox, to the Ask The Audience option in Who Wants to be a Millionaire?

But all of these examples are somewhat artificial, because they involve decisions that are made in a social vacuum. Indeed, James Surowiecki, author of The Wisdom of Crowds, argued that wise crowds are ones where “people’s opinions aren’t determined by the opinions of those around them.” That rarely happens. From votes in elections, to votes on social media sites, people see what others around them are doing or intend to do. We actively seek out what others are saying, and we have a natural tendency to emulate successful and prominent individuals. So what happens to the wisdom of the crowd when the crowd talks to one another?

Andrew King from the Royal Veterinary College found that it falls apart, but only in certain circumstances. At his university open day, he asked 82 people to guess the number of sweets in a jar. If they made their guesses without any extra information, the wisdom of the crowd prevailed. The crowd’s median guess was 751.* The actual number of sweets was… 752.

This collective accuracy collapsed if King told different groups of volunteers about what their peers had guessed. If they knew about the previous guess, a random earlier guess or the average of all the earlier guesses, they overestimated the number of sweets. Their median guesses ranged from 882 to 1109. King likens this effect to real-world situations where people collectively drive the prices of items above their value and create economic bubbles. It’s what happened to create the recent US/British housing market crash or, more historically, the tulip mania of 17th century Holland.

Jan Lorenz recently found the same thing. Swiss college students can form a wise crowd when answering questions independently, but once they could find out what their peers had guessed, their answers became more inaccurate. In his summary of the study, Jonah Lehrer wrote, “The range of guesses dramatically narrowed; people were mindlessly imitating each other. Instead of canceling out their errors, they ended up magnifying their biases, which is why each round led to worse guesses.”

Is the crowd doomed to groupthink? Not quite. King found that he could steer them back towards a wiser guess by giving them the current best guess. When this happened, the median returned to a respectable 795. So the crowd loses its wisdom when it gets random pieces of information about what its members think, but it regains its wisdom if it finds out what the most successful individual said.

King says that this mirrors what happens in real life. The crowd may be a social beast, but it isn’t an indiscriminate one. Certain individuals wield disproportionate influence, and groups of soldiers, employees, players and even animals often rely on leaders when they make decisions.

There’s a reason for this. When King provided his volunteers with the best previous guess, their range of answers was narrower with fewer extreme predictions. Their collective answers were also about as accurate in small groups of 10 people as they were in larger ones of 70. King writes, “Copying successful individuals can enable accuracy at both the individual and group level, even at small group sizes.”

But King’s study still reflects an artificial situation, because he knew beforehand what the right answer was and could provide the crowd with the closest guess. Real crowds rarely, if ever, have that luxury. If anything, this results simply reiterates how important it is to choose who we emulate. If we pick poorly (like the crowds who learned about a random earlier guess), our decisions are worse. If we pick well (like the ones who learned about the best previous guess), we fare better. You can insert your own modern case study here, but perhaps this study ends up being less about the wisdom of the crowd than a testament to the value of expertise. Maybe the real trick to exploiting the wisdom of the crowd is to recognise the most knowledgeable individuals within it.

* Yes, I’m using the median. The last time a science writer did this for a wisdom-of-crowds story, the internet erupted. For anyone not convinced by the median, this post by Josh Rosneau lays it all out clearly. Stats junkies can pore over the data for themselves in the image below.

Reference: King, Cheng, Starke & Myatt. 2011. Is the true ‘wisdom of the crowd’ to copy successful individuals? Biology Letters http://dx.doi.org/10.1098/rsbl.2011.0795

Image from despair.com