The Future of Everything: The Science of Prediction

by David Orrell

  Coral reefs will turn white.10

  Losses in species diversity will result in widespread ecosystem collapse.11

  Global warming will accelerate disease spread in a range of species, from coral to Hawaiian songbirds.12

  Dengue fever, malaria, and other mosquito-borne tropical illnesses will head north.

  The increased incursion of humans into natural habitats will bring new and deadly diseases.13

  Biotechnologists will accidentally or deliberately create novel pathogens that will be released into the population.14

  Our increased population density, coupled with rapid trans portation networks, will result in fastspreading pandemics.

  The gap between rich and poor will accelerate, leading to increased social and economic instabilities.

  The NASDAQ stock index will reach one million.15

  Poor people will cluster in vulnerable areas, and the number of lives lost to natural disasters will continue to climb.

  Wars will erupt over water, as well as oil.16

  Local shortages of food and water will lead to mass migrations.

  Climate disruption, unsustainable land use, ecosystem collapse, population growth, pollution, and other factors will combine to reinforce one another and accelerate the degradation of the planet.

  An asteroid at least fifty kilometres wide will collide with the earth sometime during the century, killing millions of people.17

  The release of tiny, self-replicating machines invented by nanotechnologists will reduce the surface of the planet to a “grey goo.”18

  There will be a nuclear war, followed by a nuclear winter.19

  Civilization will collapse globally.

  Other things to look out for are the following:

  The average global temperature will be little changed.

  The growth in global communication, coupled with increased interest in the environment, will help slow or reverse environmental damage.

  People will switch to fuel-cell carsPeople will switch to fuel-cell cars or hybrids or bicycles or foot-power or public transit or stay at home in huge numbers.

  Countries will become far more efficient in energy use, embracing non-carbon energy sources such as solar, biomass, wind, etc.

  Countries will switch to nuclear reactors, perhaps based on fusion technology.20

  Most cancers will be curable or treatable in rich countries.

  Stem-cell and other genetic treatments will extend the lifespans of wealthy people.

  Nanomachines will help control global warming by removing carbon from the atmosphere (before they convert the earth’s surface to a grey goo).

  We will rapidly evolve taboos against pollution and overpopulation.

  Partly as a result of a booming global economy, birth rates will fall more quickly than anticipated. The earth’s population will not be much greater than today’s.21

  Carbon emissions will stabilize.

  We will experience a revolution on the scale of the agricultural and industrial revolutions.22

  Civilization will prosper globally.

  The NASDAQ stock index will cease to exist.

  The earth system will recover quickly from the damage we are doing.

  The earth system will cure itself, in a way that is bad for us.23

  Finally, we might:

  begin to see the planet as a living system, and as a result stop damaging it.

  denounce our oracles as false, deluding, and distracting —or simply stop listening to them

  Except perhaps for the last, these predictions are consistent with GCM forecasts and IPCC projections under different economic scenarios, but represent only a sample of the known unknowns. There are, of course, also the unknown unknowns.

  Given that we can rule none of these out, how can we determine the probability of any of them happening? Is the chance that global warming will be greater than 2°C just 10 percent, or is it more like 90 percent? What exactly are the odds?

  Robert FitzRoy defined a forecast as something completely objective, “the result of a scientific combination and calculation.” But as I argued in this book, we cannot obtain accurate equations for atmospheric, biological, or social systems, and those we have are typically sensitive to errors in parameterization. By varying a handful of parameters within apparently reasonable bounds, we can get a single climate model to give radically different answers. These problems do not go away with more research or a faster computer; the number of unknown parameters explodes, and the crystal ball grows murkier still. There is no State of Civilization Risk Assessment Test (SOCRATES) to tell us the answer. We can’t mathematically calculate the odds, even if it looks serious, scientific, and somehow reassuring to do so. Like Socrates himself, we only know that we know nothing. Any prediction necessarily involves a large dollop of subjectivity. Numerical models are not enough.

  One way forward is to ask experts what they think. This is the approach of the IPCC, who asked themselves. Based on “collective judgment of the authors, using the observational evidence, modeling results, and theory that they have examined,” the IPCC concludes, for example, that there is a 90 to 99 percent probability of “increased heat stress in livestock and wildlife” because of higher maximum temperatures, but only a 67 to 90 percent chance of “increased damage to coastal ecosystems such as coral reefs and mangroves” because of more intense tropical cyclones.24 Such fuzzy estimates are a useful way to present complex information and attempt to rank threats. However, the results are panel-dependent, and not everyone shares the IPCC’s robust belief in the models. A group of economists would probably conclude that in a hundred years, we and our livestock will all be living in air-conditioned bubbles, and a panel of skeptics would insist that we will acclimatize to slightly warmer conditions. A panel consisting of Astronomer Royal Sir Martin Rees, meanwhile, would give us only a 50 percent chance of surviving at all, which puts things into perspective.25

  To get a balanced assessment, we have established a panel of enlightened, rational, far-sighted experts—the true paragons of reason. Yes, we mean you, the readers of The Future of Everything. Please join the online forum at www.apollosarrow.ca to vote on issues from the likely extent of global warming and the chance of a global pandemic to the probability of a major shift towards a sustainable economy. We will tabulate the responses in real time and use them to formulate a prediction. The result will be carefully archived. It may not predict the future, but will at least provide amusement for anyone from future generations who happens across it.

  GREAT PREDICTIONS FROM HISTORY

  No book on prediction would be complete without a salute to famous predictions from yesteryear.

  “If one might trust the Pythagoreans, who believe in the recurrence of precisely the same series of events, you will be sitting there, and I shall be holding this staff and telling you my story, and everything will be the same.” —Eudemus, a student of Aristotle, commenting (around 300 B.C.) on the Pythagorean notion of eternal recurrence. That would explain those faint feelings of déjà vu.

  “Whatever befalls the Earth, befalls the sons and daughters of the Earth.” —Chief Seattle, 1854. Not a prediction so much as a warning.

  “When the Paris Exhibition closes, electric light will close with it and no more be heard of.” —Erasmus Wilson, Oxford University, 1878. Electric lights are now visible from space.

  “The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth and reasonably expect their early delivery upon his doorstep; he could at the same moment and by the same means adventure his wealth in the natural resources and new enterprises of any quarter of the world, and share, without exertion or even trouble, in their prospective fruits and advantages.” —John Maynard Keynes predicting Internet commerce, around 1900.

  “The horse is here to stay, but the automobile is only a novelty.” —The president of the Michigan Savings Bank advises against investing in the Ford Motor Company, 1903.
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  “Sooner or later a crash is coming, and it may be terrific . . . . Factories will shut down . . . men will be thrown out of work. . . . The vicious circle will get in full swing and the result will be a serious business depression.” —Roger Babson, 1929. His remarks came before the worst crash in U.S. stock-market history—and may have helped trigger it.

  “I think there is a world market for maybe five computers.” —Thomas Watson, 1943. A good thing for this chairman of IBM that he was wrong.

  Computer chips should double in power at a rate of “roughly a factor of two per year.” —In 1975, Gordon E. Moore modified his 1965 prediction (otherwise known as Moore’s Law) to a doubling every two years. It has proved quite accurate. If computer-based predictions had kept pace since the 1950s, they would have improved by a factor of a million, and we would be able to see into the next century.

  “By the year 2000, people will work no more than four days a week and less than eight hours a day. With legal holidays and long vacations, this could result in an annual working period of 147 days worked and 218 days off.” —From the New York Times, October 19, 1967. If only we could get away from those computers.

  “Genetic control or influence over the ‘basic constitution’ of an individual.” —First predicted in 1967 to be available by the year 2000, it was assessed by a panel of scientists in 2002 as “a prediction that might occur, but hasn’t happened yet. ”26

  “There is now considerable evidence that the first stages of the next ice age may really begin soon, within the next few years—and that the transitional stage of extreme and inhospitable climate may already have begun.” —Larry Ephron in The End: The Imminent Ice Age and How We Can Stop It (1988). Global warming put a stop to that.

  We are “moving toward the greatest worldwide depression in history, in which millions of people will suffer catastrophic financial reversals. . . . It will occur in 1990 and plague the world through at least 1996.” —Ravi Batra, talking up what became a huge economic boom, in The Great Depression of 1990 (1987).

  “You can live long enough to live forever.” And see the future yourself. An optimistic (I think) 2004 forecast from the anti-aging guru Ray Kurtzweil. So long as you remember to look each way before crossing the road, from now until the end of time.

  THE FUTURE FORETOLD (FOR NON-MATHEMATICIANS ONLY)

  In the meantime, allow me to probe the tangled entrails, the whispering trees, the babbling brooks of subjectivity for omens and portents and wholesome advice. . . .

  I feel we’re living in a bubble, but I can’t prove it, and I can’t call the top. I think, at a global level, we won’t run out of energy, water, or resources anytime soon, but the planet still has limits, and just because they bend (they are not fixed or immutable) doesn’t mean they won’t break. I think we will affect the climate, and not be best pleased with the warm and erratic outcome. But the real problems will be down here on the ground, not up there in the sky. I think we won’t be able to produce detailed and convincing predictions of the changes before they happen. I think we should have fewer children, pollute less, tread more lightly—and not wait for our scientists to compute us a solution. It’s a time for action, not calculation. I feel a storm is coming, but I don’t know if it is atmospheric, medical, economic, or all three. I feel we’re in only the second act of this particular story—tension is building, forces are aligning, clouds are gathering—and it’s not clear what twists lie ahead or how matters will resolve. I think nature has a few tricks left up her sleeve.

  I think this is pretty unoriginal (it’s not rocket science), but I can’t prove it objectively, rationally, or mathematically, because it’s not that kind of problem. Life is not a predictable machine. Life is a surprise.

  But . . . when Kepler asked his tutor, Mästlin, for advice on astrological predictions, he told him just to predict disaster, since that was bound to come true sooner or later. So a disaster: sometime in the next hundred years, just when overpopulation and environmental stress seem to be the biggest problems, and many in poorer countries are weakened by drought and famine, there will be a worldwide pandemic. Our global, interlinked, just-in-time economic system will fall apart as countries impose quarantines and people stay at home. A couple of years later, when the disease has run its course, we will try to start up the economic machine again—but rust will have set in. Carbon emissions will decline, and the climate will eventually stabilize. After a period of wars, invasions, and insurgencies, so will we. Life will return once again to normal, with the difference that we are wiser, more humble, and more respectful of nature.

  And then we’ll do it again.

  Or, scenario B—and here I embrace the non-objective, ensemble-forecasting approach—we get a warning shot that we can’t ignore. This kick-starts a third, already nascent revolution, one that’s of the same magnitude as the agricultural and industrial revolutions but does not involve a new way of extracting energy from the ground. We’ll know it after we see it. Carbon emissions will decline, and the climate will eventually stabilize.

  DEFENCE OF SOCRATES

  As we’ve seen in this book, mathematical models have consistently failed to provide accurate predictions of atmospheric, biological, or economic systems—they do not know the future. Such a statement usually has negative connotations: “I don’t know” is associated with failure, bad marks on exams, and in Socrates’ case, the sipping of poisonous hemlock drinks. But it does not mean that mathematical models are of no use in addressing the world’s problems or understanding the present. Our impact on the planet can be visualized only with scientific technology that extends our senses to a global level. The important thing is that we do not allow an unbalanced and often fake insistence on objectivity to distance us from the world or cut off our connection to it. The future depends on the choices we make, and on the reactions of complex systems that are beyond our control. Decision-making in such situations relies as much on felt cultural and political values as it does on logical analysis. Objectivity and subjectivity must be in balance, and inform each other, just like the positive and negative feedback loops that characterize living systems. We will choose to protect nature only if we value it—and not just as an object, but because it is alive. The only way we will respect it is if we understand that we cannot control it.

  In non-linear, complex systems, change often happens abruptly, like water turning to ice. Extreme change is normal. This makes prediction difficult, but it also holds out tremendous hope, because it means that a sudden change in course can be expected. Such change often comes from the bottom up, rather than from the top down; it comes as a felt reaction, rather than something told to us by experts. Unlike deterministic mechanical systems, we have a choice; we can determine our own destiny. We are not slaves to the initial condition, our genes, or the efficient market. We are unpredictable, and that’s no bad thing.

  The science of complexity will not build a better GCM, and neither will Gaia theory or earth system science. Their stories are more of humility than of human ingenuity. But if we as a species are standing at a precipice, it is better that we see the world feelingly than be completely blinded by our mental models; that we know what we do not know.27 Creativity often emerges from a state of uncertainty. Grasping for illusory knowledge by over-modelling our environment is therefore part of the problem.

  Even if we cannot predict storms, we can predict our ability to weather them. Engineers can calculate the vulnerability of structures to disasters such as flooding, hurricanes, and tsunamis, and help design suitable building codes. Economists can point out weaknesses in a country’s financial system, and health workers can determine how much medicine will be needed to fight an epidemic. But as our populations extend into floodplains and coastal areas, and global warming raises sea levels and increases the force of storms, we may find that the walls we built to withstand those once-in-a-lifetime storms are no longer high enough to keep the water out.

  Mathematical models will always be indispens
able. Like language, they are a way to understand the world, and organize and communicate our thoughts. They help us perform hypothetical experiments, explore possible scenarios, and expose fragilities. Most of all, they help us comprehend what is happening now. The mathematician Ralph Abraham wrote: “While we may not be able to predict the future with certainty, or at all, we may at least exercise our cognitive processes, with mathematical models and computer graphic simulations that improve our understanding of the present, enhancing our chances of survival in the future.”28 Apollo’s arrow cannot fly into the future or protect us from plague, but it may serve as a compass, point out dangers, and help us navigate an unpredictable world.

  APPENDICES

  These appendices present three conceptual models that illustrate some of the ideas in the book. The first is based on bread-making, the second on the flow of air, the third on the growth of daisies. Each tells a simple story, like a fable, and has its own moral.

  APPENDIX I: THE SHIFT MAP

  The shift map was introduced in Chapter 3 as a simple example of a chaotic system. The dynamics, which are similar to the kneading of bread dough, were illustrated in figure 3.2 (see page 100). The first few iterations, for two nearby initial conditions, are shown in the left panel of figure A.1. The solid and dashed lines could represent the positions of two yeast cells in the dough, on a scale from 0 to 1. They start close together, but after just a few iterations, they are completely separated.

  Now, suppose that we wish to predict the future location of the daughter cell (dashed line in the left panel), based on the position of the mother cell (solid line). Over the first few steps, the error will increase exponentially. The solid line in the right panel shows the average error growth over a large number of experiments from different starting points, for the same small initial error of 0.005. The average separation indicates what we could expect the prediction error to be after a certain number of iterations. As seen, the exponential growth eventually saturates at the average distance between two randomly chosen points. This is ID="275">