There’s been a bit of a debate over population predictions on last week’s review of Peoplequake. Among the bones of contention are the UN population estimates, and a 2005 UNEP report on environmental refugees, currently the subject of much skeptic tub-thumping.
Making predictions is a tricky business, but it’s also a natural and necessary process. Reading the future is not a mystical exercise for soothsayers. We do it all the time. If you want to plan ahead in anything, you have to make some kind of judgement call about the future. Should I take an umbrella with me on my walk to the newsagents? Do I need to buy a pint of milk while I’m there? The answers to those simple questions will be founded on current circumstances, previous experience, and educated guesswork.
This is true on the macro level as well as the micro. As individuals, families, towns, nations, and as a species, living well in the present depends on us remembering the past and anticipating the future.
The bigger the scale, the greater the consequences of getting it wrong. I don’t have any great problem with the local council’s estimate of the number of school places needed for 2015, but there is a closed-down school site near my house from a previous over-estimate. On my way to London, I regularly have cause to lament the underestimating of passenger numbers by the train company, as a four-car train pulls into an eight-car platform. A closed school and an overcrowded train are the result of complex predictions gone wrong, and they’re expensive and inconvenient mistakes.
The biggest scale of all is predictions that affect the future of the planet. They carry the most serious consequences, and they’re the most complex and the most controversial. There’s no single body responsible for species-wide planning, but a patchwork of international institutions, government departments, think tanks, NGOs and research institutes. There are patterns of behaviour affecting our future, and being able to read them and respond is vital. Feeding the world, stewarding resources, protecting species, keeping the climate in balance, protecting human life and avoiding conflict – all of these depend on long range forecasting, identifying trends, and drawing up policy accordingly.
We can’t afford not to read the future like this. Neither do we want to get it wrong, not least because a false prediction undermines future warnings. There are fresh predictions in the papers every week, on both dangers and good news, growth forecasts and profit expectations. So how do we tell good predictions from bad ones? How do we spot truth from guesswork? Danger from alarmism? How to judge undue pessimism or optimism?
Here are a few standards by which to judge predictions:
- What is the actual source?
There are at least three levels to a prediction. It probably originates in science, and a balanced, carefully worded extrapolation or observation. For example, an arctic scientist might observe that “If every summer ice melt was as severe as 2007, there would be no Arctic summer ice left by 2015” The university press office spots an opportunity to score some publicity for their institution: “Scientists warn of Arctic sea ice collapse by 2015”. Then the journalists add a third level of spin to the press release, and the headline comes out as “Ice-free Arctic by 2015”. Never take a newspaper story at face value and always take a press release with a pinch of salt. The truth of it, if it’s there to be found, will be in the original study or report. If it’s a sensational story, it’s likely that there’s a frustrated scientist somewhere at the end of the chain who actually said nothing of the sort.
- Is the prediction conditional?
Honest predictions are always conditional. If we carry on, this will happen. The unspoken counterpoint is of course that if we do change, it won’t happen. It’s a matter of humility and a way of covering your back, but it’s good science too, as science is an evolving discipline. It recognises that we can’t see the future, and that our guesses about it are tied to current trends. Smart predictions should include variables or alternative scenarios as much as possible, and recognise that things can change. Most scientists are only prepared to give quite narrow predictions, and it’s the series of ‘ifs’ that precede a prediction that are the measure of its success or failure.
- How much data underpins the trend?
Most predictions are extrapolations of a trend, so the key question is whether or not there is sufficient data to detect one. Until 2010, you could start your temperature chart at the record high of 1998 and display a cooling trend. Or you can start your chart with the dire ice melt of 2007 and claim that Arctic ice is making a recovery. At the level of climate or demographics, it takes decades to form and identify a trend. The longer the data record, the more reliable the prediction.
- What is the agenda? This is a matter of reputation. Some scientists are always firing off dire prognostications, and you have to wonder why. A sensational claim is a great way to make a name for yourself. It doesn’t mean it’s false, of course. It means we need to look at the track record of the predictor, or the institution backing their work. And where was the claim made? Was it originally made in a peer-reviewed paper, or was it announced in a speech or a book launch?
Of course, it’s possible for something to be responsibly worded and based on sound data, and still be wrong. It’s a delicate art. Predictions alone aren’t enough to make our decisions. We need to balance it with risk analysis, the cost of action and the cost of inaction, but that’s another story. As a final precaution against making rash predictions, here’s a Google search engine view of the future, compiled by XKCD.