The Norm Chronicles (41 page)

One thing is certain for children born in the future – there are going to be a lot of old people around for them to look after, as those already plodding through their middle age are not going to go away. The UN
estimates that the proportion of people over 60 will double between 2007 and 2050, as people will live longer and lower fertility rates mean fewer young people.
⁹
There will be 2 billion people over 60 in the world by 2050, and around 400 million people over 80.

But what sort of state are all these old people going to be in? After the bit about three-score years and ten, Psalm 90 continues with ‘and if by reason of strength they be fourscore years, yet is their strength labour and sorrow; for it is soon cut off, and we fly away’, which doesn’t exactly paint an encouraging picture of ageing. Are we making all this effort to live longer just so that we can spend even more time sitting round the edge of a room, television blaring, struggling to grasp what reluctant visitors are shouting at us?

Recent studies have suggested a more positive view of health: 78 per cent of an unselected group of over a thousand 85-year-olds in Newcastle upon Tyne reported their health as at least ‘good’ compared with others of their age,
¹⁰
and only 16 per cent suffered from depression.

But 61 per cent lived alone, and loneliness is associated with failing mental abilities, probably feared even more than physical disability. This is already a big issue and won’t become any easier: 30 per cent of over-90s have dementia, and the number of people in Britain who are over 90 is predicted to rise from 1.2 million in 2010 to 1.8 million by 2051.
¹¹
In 2005 it was estimated that 700,000 people were living with dementia in the UK, and this is likely to rise to 1.7 million by 2051, nearly all of whom are alive now.
¹²
Perhaps you are one of them.

In 1958 Paul McCartney saw 64 as near the end of life, whereas baby-boomers who were born just after the Second World War and have now reached this age tend to have a reasonable lifestyle and only see themselves as ‘middle-aged’, with much more before them than a precipitate decline. In 2008 UK men at age 65 had around 17 years of life expectancy left, 10 of which would be considered ‘healthy’, while women had more than 20 years left on average, 11 of which would be ‘healthy’
¹³
– ‘healthy’ means that people consider their health as ‘good’ or ‘very good’ on a 5-point scale, which is quite a stringent criterion.

So what should these people be getting up to? Oddly, the proximity of death makes risk less risky. That sounds strange. But if you looked
simply at relative risk probabilities, you could almost conclude that the old should be out there playing with fire. Here’s how that surprising calculation works.

Recently DS was asked to do a tandem sky-dive for a TV programme and, of course, checked the data. Sky-diving is on average around 10 MicroMorts (see
Figure 36
), but he reckoned tandem would be a bit safer (only 1 death in 340,000 tandem jumps recorded by the British Parachute Association
¹⁴
). So he reckoned around 7 MicroMorts for the plane ride and jump.

For a young lad of 18 (average total annual risk of death from all causes 530 MicroMorts) this is equal to around 5 days of average background risk, whereas for a man DS’s age (all-cause annual risk 7,000 MicroMorts) it is only around 9 hours’ worth. So, from a relative perspective, it makes more sense for an old codger to hurl himself out of a plane, charge around on a Harley-Davidson and play chicken on motorways than some cocky youth with their life ahead of them. But try telling that to the youth.

27
JUDGEMENT DAY

W
E
–
THAT IS, THE AUTHORS
– have a problem: we like numbers and we think they matter, but we like our characters too. Call this vain – we invented them, after all – but Norm, Prudence and the Kevlins are mostly all right, we think. More than that, although we recognise the patterns in numbers as well as anyone, we can’t bring ourselves to say that any of our characters is irrational by choosing to ignore them and going their own way.

It’s become fashionable to blame people for their cognitive biases or failures of reasoning, but we think that much of what it’s tempting to call irrationality about danger is really a result of the way the information is framed, or the sheer complexity of the decision, and that their reasoning is usually reasonable, for all their human ways.

It’s not reasoning that we would necessarily share, but nor is it reasoning we can easily dismiss. You can call Norm a berk if you like, Kelvin a smug, offensive slug and Prudence a pain in the arse – though we think they deserve more understanding than that – but given what they want from life, we don’t know how to prove that any of them is actually
wrong
about the choices they make in the face of danger. We don’t know how to use data to tell them how to live. Even if planes feel more dangerous to travel in than cars, it’s not much use to point out to any individual that the probabilities of fatality are the other way round, since what they mean by danger is seldom as simple as a mortality rate. It is often, as we’ve said, not even about danger.

They may be odd, but they are not stupid, they know what they care about. They live in an uncertain world, where risks can change and no one knows which side of the odds they’ll fall. Their hopes and fears are not like the unfounded fears of monsters under the bed; they are fears in a real and usually messy human context.

This is not to turn all aspects of danger into relativism. Our view is that planes really are safer than cars, on average. We simply argue that a measure of what people call risk must be a matter of personal value and personal framing. The objective numbers can’t be separated from subjective perception. A risk stated as 1 in 400 can’t help but focus attention on the 1. To say that the risk is the same if we describe it as a chance of 399 in 400 of nothing happening might be mathematically correct, but when people react to these different frames differently, that does not, in our view, demonstrate their irrationality. It demonstrates the importance both of the numbers and of perspective. Think of it like the view of the countryside from the city, compared with the view of the city from the countryside. Both country and city exist in the same proportions wherever you stand, but that doesn’t mean that where you stand is irrelevant. The view matters. So do the proportions. Risk does not exist independently of the way that people see it. Nor can the way they see it float free of the numbers.

We could go further. We looked at a lot of numbers to write this book – and we mean
a lot
– and we have a geeky streak ourselves. Possibly you noticed. Maybe that leads you to expect that our private attitude to risk will be on reason’s side. And on the whole it is. But while we think the numbers are vital, we are not piano keys either, and we share a deep sense of the uncertainties around data, statistics and evidence. Whether you think that chance really exists, or that your fate was cast in the Big Bang or that it’s all fixed by a deity or three sisters spinning, measuring and cutting your fate, we all still have to deal with not knowing quite what will happen. We think there’s more uncertainty than you’d think from the way people throw numbers around.

We think this especially because when you try to grab hold of probability it somehow slips through your fingers. It’s hard to say what it really is for an individual. It’s hard, too, to say how the average affects any individual.

Of course, some things are more likely than others: the chance of getting wet if it rains compared with being – alone of 7 billion people on the planet – the one to cop an asteroid. Ignore these differences and we would worry about you. It shouldn’t have taken until the 1650s, when Blaise Pascal and Pierre de Fermat began a correspondence about dice, for people to get round to putting numerical probabilities on events. But although in some ways it is a simple idea, it has caused headaches ever since.

As an example, on 14 April 2012, DS saw a tip in a newspaper and put £2 on Cappa Bleu to win the Grand National at Aintree. The odds were 16 to 1, which meant a profit of £32 for a win, but could also be interpreted as meaning that the bookmaker thought there was a ‘chance’ of around 6 per cent that Cappa Bleu would win.

Previously, DS had been to see his general practitioner, who measured his blood pressure and cholesterol, tapped at his computer and duly announced a 12 per cent chance of a heart attack or stroke in the next ten years. Disturbing … until the GP also said that this was less than average for a man of the Professor’s age, who then irrationally cheered up at this change of framing. After a strong finish, Cappa Bleu came in fourth.

But what do all these probabilities mean? Philosophers and statisticians have argued for centuries and are far from agreement. Into this sometimes savage controversy what can we do in a short space but charge, prejudices blazing? Here are ours, which mirror how we feel about Norm, Kelvin and Prudence.

Traditionally, probabilities have been based on known physical properties and pure reasoning – for example, a coin has two sides, so tossing it has a 1-in-2 chance of coming down heads; throwing a dice has a 1-in-6 chance of a six; dealing one card from a (properly) shuffled standard deck of cards has a 1-in-52 chance of turning up the ace of spades. But this only works if we start with some idea of ‘equally likely events’, in the sense that all cards are somehow equally likely to turn up. But that requires us to say what ‘likely’ means, so we’re back where we started. (And then, of course, in real life someone might cheat.)

Another idea of probability is to say that it is how often something
happens when a similar situation is repeated a vast number of times, such as the proportion of people who reach 100 years of age. But apart from very special set-ups such as flipping coins, these exactly similar situations just don’t occur: there is only one you to reach 100, or not, only one Grand National that DS could bet on in 2012, and only one DS to have a heart attack, or not. The idea that we all conform to the frequencies of the dead takes most of the life out of life. What was is not necessarily a good guide to what might be, let alone what will be.

As a way of dealing with the one-offs that we all like to think we are (yes, we are all individuals) some philosophers offer the idea of an intrinsic tendency for an event to occur, so that all the vastly complex aspects of DS’s current and future existence combine to give some sort of ‘propensity’ for him to have a heart attack or stroke in the next ten years, and the doctor’s ‘12 per cent chance’ is an estimate of this. The idea of Cappa Bleu having some true underlying propensity to win is attractive but does not seem useful or provable.

We reject all these explanations and take a very pragmatic stance – that this ‘12 per cent chance of a heart attack’ is not really DS’s risk, and not even an estimate of some propensity of it. It is based on a few items of limited information, and should be treated like the ‘probability’ of Cappa Bleu winning – reasonable betting odds given current information. No more and no less.

Treating probability like a bet seems a cop-out, but it has powerful implications. It means that any number we claim for a ‘probability’ is constructed by us based on what we know. It is necessarily a judgement and does not exist as a property of the outside world. Risk, in this sense, is a measure of what we don’t and can’t know as much as a measure of what we can.

All of which forms part of a rather startling conclusion: that independent, objective probability, as Norm says at the last, doesn’t exist.
*

Nor, as we say, does the average person exist to whom the average risk is supposed to apply. The average is an abstraction. The reality is variation. Poor Norm, he was a man in search of data, but perhaps the data were really in search of him. Was he ever really there? He had to disappear once he finally stopped believing in the norm.

In some ways probability is a bit like the certainty that there will be people, the story with which we began, but a certainty that tells you nothing about who. In other words, it tells you only a tiny part about you. The probability that there would be at least one person called Norm – high – is only a tiny part of the story about how this particular – infinitely improbable – Norm came into being.

So in practical terms, for the events of life in general, when we say a certain activity is dangerous and quote its risk as so many MicroMorts, these numbers should be considered only as reasonable betting odds given what we know. As soon as we know more – maybe the age of the person about to try base-jumping and whether they are sober, or how many pike there are in the reservoir, if they’re near by, how fast they swim, when they last ate, whether the particular one that hasn’t eaten lately still feels hungry and is near enough and fast enough and is the sort to recognise the edible potential of human flesh, even disguised by sagging underpants,
and
is a hard-nosed, vicious-enough, brave-enough sod to go for a lad’s tackle – the risk changes, suggesting that the potential degree of refinement is often infinite. And this can just as easily be applied to things that have happened but we don’t know about yet, such as giving the odds that Jack the Ripper was really the duke of Clarence. Or Queen Victoria, for that matter.

Nor can any single risk capture the full complexity of our feelings and judgements about nature or the economy – or let’s go the whole hyperbolic hog and add the meaning of life – and so none of the natural, economic, lifestyle or other risks that we talk about can be explained except in the context of a vast swathe of other values. Our psychological reactions can be both optimistic (Kelvin and sex) and pessimistic (Norm and pike), and who knows in any instance which will apply? Similarly, no calculation of probability
times
consequence can tell you what weight you should attach to the consequences – in the unlikely
event that you know them all – a weight that can only be for you to decide. And if half the calculation of a risk is infinitely variable, what is the objective answer to that calculation?