So, what’s going on? “The wisdom of the crowd is well known,” says Toby Walsh, an artificial intelligence researcher at the University of New South Wales in Sydney, Australia. “Various methods have been developed to tap into collective smarts.” One example is prediction markets, where individuals make financial bets – on the stock market, say – based on the outcome of a future event. The overall market behaviour can be used as an indicator of the probability of that event.

And in 1999 – three years after losing to IBM’s Deep Blue computer – chess master Gary Kasparov took on a crowd of 50,000 people over the internet. He won, but said he had never before expended so much effort in a game and called it the greatest game in the history of chess – thanks to the sheer number of ideas and different viewpoints.

In fact, the idea goes back at least 100 years. In 1906, the polymath Francis Galton asked 787 farmers to guess the weight of an ox. Their guesses were all over the place but the average of all of them was only a single pound off the correct answer of 1,197 pounds. A few years ago, US National Public Radio repeated the experiment by asking more than 17,000 people to guess the weight of a cow in a photograph. Again, the average was remarkably close – within 5% of the correct weight. And in this case, the crowd was not made up of farmers.

Educated guesses are clearly part of it. Yet – as with the NPR stunt – the participants in Rosenberg’s experiments are not experts. Nobody in the group that predicted last year’s Oscar winners had even seen all of the winning films, for example.

More importantly, relatively small swarms consistently outperform much larger crowds. Last year Rosenberg put the cow question to a swarm. With a pool of just 49 people, the accuracy of the guess more than doubled when acting as a swarm compared to simply averaging the group's responses. It’s more than just the wisdom of crowds, says Rosenberg. “We make groups of people smarter.”