While accepting the Nobel prize for economics, Friedrich Hayek made an astonishing admission. Not only were economists unsure about their predictions, he noted, but their tendency to present their findings with the certainty of the language of science was misleading and “may have deplorable effects”.

This revelation, made about 40 years ago, is a crucial one and yet it has been largely forgotten or ignored. One of the most striking comments before the EU referendum was from Michael Gove. He claimed people in Britain had had enough of experts. This has since become something of a mantra, and polling does indeed suggest that most people place little trust in expert predictions and pronouncements.

One of the problems with economic forecasting is that a small change in a few variables can make predictions almost impossibly complex. To understand how quickly the maths can become complicated, Prof Sir Michael Berry tried to forecast the path of a snooker ball after it was hit. Guessing where the first ball would go was easy; the second impact became more complicated, but still possible. The problem was that to correctly forecast the ninth impact, you would need to take account of the gravitational pull of someone standing nearby. To predict the 56th, you would need to include the effect of every single particle in the universe.

So how do you make good predictions? I met “superforecaster” Michael Story, who was ranked 18th best among the 20,000 people who formed the Good Judgment team. The team took part in a competition conducted by the US intelligence community to find the world’s best forecasters. Launched in 2011, the four-year contest required the group to provide forecasts on 500 questions ranging from the future for oil prices to the financial outlook. The Good Judgment team won the tournament, reportedly outperforming even professional intelligence analysts with access to classified data.

The grading of their volunteers’ forecasting abilities was key to why Good Judgment did so well. People knew how well they were performing and were driven to improve. They were also encouraged to correct their biases and alter their world view amid changing circumstances. This self-analysis and willingness to adapt, they believe, was crucial to the team’s success.

Financial superforecaster Michael Story

In a world in which we rate restaurants on TripAdvisor and the effectiveness of hair straighteners on Amazon, it is curious, and perhaps dangerous, that we fail to rate the economists who provide us with the forecasts on which world-changing decisions are made. Would it not make sense to have a reliability measure for economists as we do for any number of small consumer products? That way it would offer clues as to whether a forecast was reliable.

Prakash Loungani at the IMF analysed the accuracy of economic forecasters and found something remarkable and worrying. “The record of failure to predict recessions is virtually unblemished,” he said.

His analysis revealed that economists had failed to predict 148 of the past 150 recessions. Part of the problem, he said, was that there wasn’t much of a reputational gain to be had by predicting a recession others had missed. If you disagreed with the consensus, you would be met with scepticism. The downside of getting it wrong was more personally damaging than the upside of getting it right.

Not only have we been bad at forecasting, but there is not much sign of improvement. Mark Pearson, deputy director for employment, labour and social affairs at the OECD in Paris, said: “We are getting worse at making forecasts because the world is getting more complicated.”

Increased complexity is not the only problem – forecasts are also made less trustworthy because of a feedback loop. So if a meteorologist says it will rain, the fact that you take an umbrella out with you does not affect the weather. But if an economist forecasts that inflation will rise by 3% and we react by asking for at least a 3% rise in wages, we have changed the basis on which the forecast was made. Inflation is now likely to rise by more than 3%. The fact that the forecast exists changes the reality it is trying to predict.

Perhaps what we need is economists to say something like: there is a one in two chance that this will happen, but I can’t be sure. In other words, they should embrace the uncertainty, not be embarrassed by it. Weather forecasters have started doing this. The Met Office has a precipitation probability measure that reveals how accurate a forecast is likely to be.

The Good Judgment team believes part of the problem is that we misunderstand the science of forecasting and look to the wrong people for predictions. If we want to know what’s happening to the economy, we think the obvious thing to do is ask an economist. But Storey says that may be the wrong approach. Forecasting is an art that is separate from the need to have specific subject knowledge. The people who were best at predicting the Arab spring, he said, were not Middle East experts. They were people who studied eastern Europe and had seen similar patterns develop there. We don’t need subject experts, we need people who are great at forecasting anything.

As we enter unknown economic waters, it is important to reassess how we use forecasts. Not only should forecasters reveal how confident they are, we also need to understand the limitations of the forecasts on which we are basing our businesses, votes and well-being.

• Adam Shaw is a freelance journalist whose programme on forecasting is on In Business on BBC Radio 4 on 7 September.