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Whatsapp Research shows that pundits tend not to be much good at predicting future events.

Futurists, pollsters, political pundits—there’s certainly no shortage of ‘experts’ ready to predict the future in confident and unambiguous tones. But why do they often get it so terribly wrong? Of course the data they work with could be suspect, but as Antony Funnell explains, the root cause may lie within.

In early December 1999 the Australian Department of Foreign Affairs issued an advisory, warning Australians not to travel to Russia except on essential business. Later that month they went one step further, withdrawing all but three of their embassy staff.

The warning and withdrawal was based on a catastrophic prediction: come midnight on the 31st of December 1999, all computer systems not adjusted to deal with the ‘Y2K bug’ would crash; Russia had been assessed by Australian officials as particularly and therefore vulnerable.

The future is scary because we don't know what's going to happen, and not knowing intrinsically means we feel powerless, and powerlessness and a lack of control makes any situation scarier.

In the end nothing happened.

Even in countries where no preparations were made—or next to none—life went on as usual, without incident.

In retrospect we know that the Y2K phenomenon was an embarrassing case of mass hysteria, but predictions of impending disaster were numerous and well-received. The global cost to governments and industry from the Y2K incident is now conservatively put at somewhere around the US$500 billion mark—a very costly example of the ongoing perils of prediction.

Even in the age of big data, mass surveillance and predictive analytics, our ability to forecast future events is often found wanting. For a contemporary example one need look no further than the recent UK election.

One of the first things British Prime Minister David Cameron did after his party was returned to government with an unexpected majority was to take a poke at pollsters and political pundits.

‘Some people say, in fact I've often said, that there is only one opinion poll that counts, that's the one on election day,’ Cameron declared in front of a crowd in his electorate of Witney, ‘and I'm not sure that has ever been truer than it is today and tonight.’

For Philip Tetlock, the utter failure of UK pollsters to predict the outcome of May’s general election would hardly have come as a surprise.

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Whatsapp Despite predictions the British general election would be close, the Conservative Party won a majority in the House of Commons.

Professor Tetlock, who’s based at the University of Pennsylvania, famously did a 20-year study of political predictions involving more than 280 experts, and found that on balance their rate of accuracy was little better than chance.

According to Tetlock, there are real limits on how predictable the future can be.

‘Even when you are using the most sophisticated analytical techniques, you can only get so far in predicting the future. That leaves us frustrated, it's unsettling.’

That in turn, he says, makes people more susceptible to futuristic snake oil salesmen—those who peddle a vision of the future based largely on pre-determined views, ideological underpinnings and sheer bombast.

‘It makes us susceptible to listening to them and taking them more seriously than we would if we really knew their track records. It makes us vulnerable to believe in people who are very articulate and have confidence and confidently express certain stories or an image of the future.’

Risk perception and communication consultant David Ropeik puts our ongoing trust in forecasters down to a basic human need for security and stability. Fear, he says, is the driver behind our insatiable need to know what lies ahead.

‘The future is scary because we don't know what's going to happen, and not knowing intrinsically means we feel powerless, and powerlessness and a lack of control makes any situation scarier. So against that fear, prediction supplies that false sense of control.

‘We grasp for a sense of control by pretending that we can see into the future and know what's going to happen.’

For RMIT University’s Jeff Lewis, that fear of instability which David Ropeik places at the heart of prediction has ancient antecedents. He traces it back thousands of years to the period in history known as the Neolithic Revolution.

‘What happened during that period is that humans changed from being hunter gatherers to being settled, and they started to go through a period of urbanisation,’ he says. ‘The places in which they settled actually introduced new kinds of vulnerability, particularly to variations in climate, because the places where they settled were usually in floodplains, in areas where there were substantial amounts of mineral deposits.’

According to the Lewis thesis, that dread of losing hard-won gains essentially made humans hyper-attuned to potential future threats.

‘With those increased vulnerabilities people not only changed the way they thought about who they were and their relationship to each other and to the economy and to culture; but they also radically changed their sense of the cosmos, they had what you might call a breach with nature.’

That anxious frame of mind has continued down through the millennia, says Professor Lewis, often finding its most extreme form in the sort of catastrophe-centred prediction embodied by the Y2K phenomenon; or more recently by the fear that Ebola was becoming the new Black Death; or even that the Australian economy, with a triple star rating and a relatively small public debt, is on the verge of a Greek-style collapse.

‘It's extremely corrosive, in my view,’ says Professor Lewis. ‘It's extremely dangerous because it limits the way we think creatively about the future. It limits our capacity to be self-aware, and it limits the sorts of solutions that we may be able to develop. We do have significant problems and we need to find creative solutions to developing a future which is going to be better than the past.’

While innate anxiety may fuel our need for prediction, and often force it in an extreme direction, that doesn’t fully explain why so many of the predictions we make end up so wide of the mark, however.

David Ropeik blames self-deception. Forecasters, he says, often make the mistake of believing that their act of prediction is based on conscious, objective, and dispassionate reason.

‘That's not what predicting is,’ Ropeik argues. ‘We feign careful thought and looking at the actuarial tables and whatnot, and to that extent it's a more intelligent process, but in the end the act of predicting what we can't know is not rational.

‘That's okay, it's not stupid or wrong, but it is a subjective, instinctive desire to have control over the scary unknowable future, and “rational” is the wrong adjective to describe it.’

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Whatsapp An illustration from a Bell Telephone Company publication in 1922 suggesting in the future 'students may he able to dial computers, libraries and other information repositories and get the information they need'.

New York-based researcher Duncan Watts also points an accusative finger at hubris: ‘I think that we can all think of examples of where overconfidence in some sort of particular theory of the world has led governments and others into catastrophically bad decisions.

Watts, a former professor of sociology at Columbia University and currently a principal researcher at Microsoft Research, says we should always be wary of strong convictions.

‘You should never be that certain about your own beliefs—the world just doesn't work that way. You have to be more adaptive, you have to be more reactive. You have to think probabilistically rather than in terms of certainties.

‘It's not that you are always going to be right, because you are going to make mistakes no matter what, but you might be less inclined to make catastrophically bad mistakes. I think that's something we can do much, much better at.’

Like Philip Tetlock and David Ropeik, Watts maintains that a major part of our difficulty in forecasting global events lies within, particularly in the way we rationalise events after the fact. It’s a theory that he's put forward in a book called Everything is Obvious Once You Know the Answer: How Common Sense Fails Us.

‘When I say common sense is misleading, what I really mean is that when we look back in the past, whatever it is that we are looking at, whether it's our own experiences or whether it's the global financial crisis or some foreign policy decision or the performance of a major company, we are always able to tell some story that makes it seem like the thing that happened was in some sense inevitable,’ he says.

‘Looking forward we are never quite sure what's going to happen, but when we look back it always seems like we should have known, that the outcome that occurred was really just a matter of common sense. If we had really just been thinking straight we would have known all along that the thing that happened was going to happen.

‘So this feeling that we have—that common sense had we been using it properly could have told us all the stuff that we missed—is actually very misleading.’

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Whatsapp Granularity is the ability to make relatively refined distinctions among degrees of probability.

The idea that a focus on probabilities rather than certainties is the best way to assure more accurate forecasting appears to have been borne out by the latest research undertaken by Philip Tetlock and his colleagues at the University of Pennsylvania.

Their latest initiative is called the Good Judgement Project and it came out of the US government agencies’ desire to improve their predictive powers.

The Good Judgement Project has involved a series of tournaments in which both experts and non-experts from a variety of fields have been scored according to the accuracy of their forecasts. The aim is to identify a set of common personal attributes among those with the highest accuracy.

The research is ongoing, involving thousands of people from numerous countries, but Professor Tetlock says there are already identifiable traits.

‘A certain amount of humility and open-mindedness is helpful, and there's something we called “granularity”; it's the ability to make relatively refined distinctions among degrees of probability.

‘If you were playing poker, for example, it wouldn't really be very controversial to say you're going to be a better poker player if you can tell the difference between a 40/60 bet and a 60/40 bet. People would say yes, that's really obvious.

‘I think it's also the case that when you are making economic policy or national security policy or whatnot, there is an advantage to being able to distinguish one side of “maybe” from the other side of “maybe”. People who can make those kinds of more subtle distinctions among degrees of “maybe” tend to be significantly better forecasters.’

Tetlock openly acknowledges that in the real world of pundits and prognosticators, any degree of equivocation is unlikely to meet with approval.

‘There is a paradox here and that is that the attributes of pundits that make them most attractive to the media make them relatively poor forecasters. The media does show a strong preference for pundits who are very confident and project with certitude an image of the world.

‘Whereas the more equivocal forecasters, the ones who have more hedges and hums and hahs, they are often less appealing to the media. They are less mediagenic. So they take a hit.’

Read more: Five reasons you probably won't like 2023

Then, of course, there’s the promise of big data.

While data arguably did little to help western governments predict the rise of ISIS, or the global financial crisis of 2007/2008, or even the result of the recent UK election, that’s not to say it’s entirely useless, says US forecaster Jay Ulfelder, who runs a popular blog about forecasting.

Ulfelder says the ability to use data to enhance prediction is improving, but he warns that all data needs to be evaluated critically, because it can be subject to mistakes or deliberate corruption. The obvious example is basic employment statistics, which Ulfelder says are widely seen as a useful indicator of a country’s stability.

Yet such statistics are often fudged by authoritarian regimes in order to paint the best possible picture of their leadership.

Still, Ulfelder remains hopeful about the ability of data to supplement forecasters’ knowledge.

‘Although the reach of big data doesn't go to all the places that we'd like it to go, it is expanding. We are getting more information from hard to track places. I'm optimistic that that will allow us to continue to make marginal improvements in how well we are doing at forecasting these things.

‘We are getting better at it, and that is why I continue to do it. Part of doing better is bringing methods to bear on the problem that haven't been applied before. We are able to do a lot more of that these days with new kinds of software and analytic techniques, as well as new forms of data becoming available.’

That may be so, but nothing, as Ulfelder himself would readily agree, is certain; after all, his prediction blog carries the self-deprecating title Dart Throwing Chimp.

The prediction predicament Listen to the first part of Future Tense's series on prediction to hear how important foreseeing the future is and why we so often get it so wrong.

We'll all be ruined! Listen to the second part of Future Tense's series on prediction to hear why our economic, political and social forecasting so often veers toward catastrophic scenarios.

Exploring new ideas, new approaches, new technologies—the edge of change. Future Tense analyses the social, cultural and economic fault lines arising from rapid transformation.



