“In a time of increased complexity and uncertainty it’s actually increasingly less likely that any one single individual will have access to all the information about what is happening,” says Peach. “But if you take a collective view by bringing together and combining the predictions of lots of different people you get to a more accurate result because they all hold different pieces of information that help to build a more complete picture overall. By combining those individual forecasts you’re also cancelling out, perhaps, some of the biases or inaccuracies that might exist in one individual forecast alone.”

Pattern recognition

The Good Judgment Project’s team of super-forecasters repeatedly made excellent predictions – so what set the individuals in the team apart from the rest? As an original member of the team, Michael Story is one of the world’s best super-forecasters. Now, he is managing director of Good Judgment Inc, the commercial spin-off of the project. “When we test people to see whether they are likely to be a good forecaster, the number one predictor of forecasting isn’t subject knowledge or anything like that, it is pattern recognition from pictures,” says Story.

By asking people to spot patterns in a series of photographs you can make an accurate assessment of whether someone is a good forecaster. But to do this, they need to be able to see past their own biases.

Story describes confirmation bias – where we selectively look for evidence to support our own ideas – as being like playing cards. How many times do you or other players say “Oh I knew you had that card” after someone reveals a winning hand? You feel certain that you knew they had those cards all along, but in reality you thought through several possibilities. When one of those is revealed you convince yourself that that was the possibility you felt most strongly about.

“I always thought I was quite good at predicting things and so on, but it is also extremely easy to convince yourself of that fact,” says Story.