Why We Lie: The Source of our Disasters. Dorothy Rowe

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СКАЧАТЬ slowed right down, hidden details are revealed. The world looks very different when time is broken down into chunks as small as 10^-43 seconds. Our eyes and our brain operate like a kind of video camera. Our eyes, like a camera, take individual still pictures, and then our brain deals with each still so quickly that we see what seems to be a continuous film. Our eyes are not fast enough to take in everything that happens within the range we are looking. We see a glass of water being thrown and what we think is the recipient’s reaction, but we do not see how, under the onslaught of the water, a person’s face takes on shapes and movements that, when revealed to us by the camera, seem quite strange. However, at whatever speed we are viewing the world, what we see is not just a matter of visual acuity. We see what is meaningful to us. When my son Edward and I were watching an episode of the BBC series Spooks, we saw one of the central characters, Ros, who was disguised as an accountant working in high finance, get into a car and drive away. We saw the car very briefly, a matter of seconds. I saw a low-slung, black convertible, and asked Edward, ‘What make of car was that?’ He said, ‘An Aston Martin – James Bond’s car.’ Cars are Edward’s passion. When I was a child, time passed very slowly. I celebrated each passing year because I wanted to grow up. Now time passes at an extraordinary rate. A day passes in a blink of an eye. Why do we have to go into the future at the rate that we do? Time seems to slow down when we are bored, or in the midst of an accident or a sudden crisis, and it speeds up when we are busy. Why can’t the speed with which we go into the future be moderated by events, better still, by our wishes? The apparent slowing down or speeding up of time in certain circumstances are examples of how our interpretations or constructions of the time we are experi encing are dependent on our circumstances. They are what Brian Cox called ‘illusions’. According to Einstein, we cannot change the speed with which we go into the future because time is a dimension we pass along, just as we can pass along the dimension of space. We cannot move through space at the speed of light, but we move through time at the speed of light. Einstein showed that we each experience the passing of time in our own individual way. As Brian Cox said, no one has the right to claim that their time is the right time.

      Einstein argued that all moments in time already exist. We are moving along time in the same way as we move along a road that has already been built. However, in the sub-atomic world of quantum mechanics, the future does not exist. Rather, it is a world of probabilities, where the future grows out of the past. Two different ways of looking at the world yield two different results.

      When Brian Cox asked Neil Turack, ‘Do you know what time it is?’ Neil replied, ‘The time today is something we have no idea about.’

      A butterfly fluttering its wings and causing a huge disaster in some distant place has become a cliché to which the word ‘chaos’ has become attached. However, for many people, the cliché is usually taken to refer to the long line of causes resulting in a chaotic disaster, as in the old nursery rhyme,

      For want of a nail the shoe was lost.

      For want of a shoe the horse was lost.

      For want of a horse the rider was lost.

      For want of a rider the battle was lost.

      For want of a battle the kingdom was lost. And all

      For the want of a horseshoe nail.

      Linear causality is so embedded in our culture that it impedes our understanding of, or even perception of, the randomness of events in our world. Many people believe that, if you win the lottery, it was not a random event, but caused by the fact that you are a good person and deserve to win. God or Fate decreed that you should win. However, the butterfly effect is not an example of linear causation. It is an example of the mathematics of chaos.¹⁴

      The development of science was based on Newtonian mathematics that describes a world that follows clear rules. It is predictable and ultimately controllable. This is the vision of the world used by those scientists and engineers who claim that the best way to deal with climate change is to devise methods of controlling the climate. Climate engineering, like the economists’ command and control economy, is one of the favourite delusions of the twenty-first century. While Newtonian mathematics works very well in a vast number of situations, there are many situations where it does not. For instance, if two objects are in orbit, it is possible to use Newtonian mathematics to predict the pos ition of these objects at any one point in time, but, if a third object is added, Newtonian mathematics cannot predict the position of the objects. In 1889 the great French mathematician Jules Henri Poincaré could not solve this problem, but he showed that, if there is any difference, however small, between the two orbits, one body will eventually fly off. Prediction is impossible.

      The advent of computers led many people to believe that all the problems in the world were soluble. All that needed to be done was to build a bigger computer. It is ironic that what revealed the flaw in this thinking was a computer.

      In 1961 Ed Lorenz, a meteorologist, using a simple model of the weather, was running some simulations of weather patterns on his computer. He wanted to run the simulation twice, so he copied what he thought were the same numbers into his computer. He had not realized that, while his computer stored numbers up to six decimal places, such as 0.473208, his printer to save space shortened the numbers to three decimal places, 0.473. This was a tiny discrepancy between the two sets of numbers, less than 0.1 per cent, but this small discrepancy changed the result. At first Lorenz thought that his computer was at fault, but he came to realize that, to forecast the weather perfectly, he would need not only a perfect model of the weather but perfect knowledge of wind, temperature, humidity and other conditions around the world at one moment in time. Perfect knowledge is never possible. No matter how accurate a measuring instrument may be, there is still a margin of error. It seems very unlikely that climate engineering will be able to control the weather and therefore climate change.

      In a similar way, a command and control economy, where a government guided by economists could ensure continuous growth in a country’s economy and so determine that a boom could not be followed by a bust, would require the careful measurement and control of those factors that drive the market, including fear and greed. The great economist J.K. Galbraith recorded in some detail the inability of the majority of the players in the market to learn from experience, but even he could not plumb the depths of economists’ failure to understand human nature. What they needed to learn was, in Paul Krugman’s words, ‘The seeming success of an economy, the admiration of the markets and media for its managers, was no guarantee that the economy was immune to sudden financial crisis.’¹⁵

      It had always been assumed that the effect of a small error in a large system would disappear. Lorenz published his findings in 1963, and in the following year another paper showed how making small changes in the parameters in a model of the weather could produce vastly different results, transforming regular events into a seemingly random, chaotic pattern. In 1972 Lorenz gave a paper at the American Association for the Advancement of Science. He called it ‘Predictability: Does the Flap of a Butterfly’s Wing Set Off a Tornado in Texas?’ Chaos, it seemed, was not a rare, random event but was there in the systems in which we live. It seems that the more complex a system is, and particularly where a number of systems are linked together, the more likely it is that, contained in the systems, is a sensitivity to initial events that leads to later events that cannot be predicted. The economic systems that led to the last run of boom years contained within them a sensitivity to events during the boom years and before, with the consequence that the fear, greed and stupidity of a hedge fund manager in New York led to a hard-working couple in Glasgow losing their jobs and their home.

      Mathematicians working in chaos theory have developed the concept of tipping point where a system is being pushed in a certain direction, and reaches a point where it suddenly tips over into another state from which there is no return. Climatologists studying СКАЧАТЬ