The Crash Course - Chris Martenson [68]
Even Sand Is Too Complicated
Even something as seemingly simple as predicting the behavior of a growing sand pile currently eludes our predictive abilities. Imagine dropping grain after grain of sand into a pile. It grows and grows, but at some point it will slump on one side or perhaps entirely collapse. Knowing when and how much seems as though it should be a straightforward task, but it’s not.
In Ubiquity: Why Catastrophes Happen by Mark Buchanan,3 a tale is recounted of three physicists, Per Bak, Chao Tang, and Kurt Weisenfeld, who set about trying to discover if they could predict when, where, and to what degree sand piles would avalanche. Using a computer model to speed things along, they ran an enormous number of simulations and discovered that nothing could be predicted at all. Not the size of the avalanche, which could range from a single grain tumbling down the face to the complete collapse of the whole pile, not the timing between events, and not whether the next grain would trigger either a cataclysm or nothing at all.
They discovered some important properties of systems that are poised on the knife edge of instability, but left the ability to predict the timing and size of catastrophic events to future scientists. For us, the important lesson learned from the sand pile experiments is that when it comes to the timing and the size of changes, complex systems are inherently unpredictable.
But this doesn’t mean they’re completely unpredictable. Knowing something of the “system of sand,” we can put some boundaries around what might and might not happen, and can therefore “predict” the future in the largest sense, even though its timing and precise details might elude us. We know that a growing sand pile will eventually collapse; we know that it cannot grow to be ten times taller than it is wide; we know that the higher and more complex the pile becomes, the more likely an avalanche becomes; we know that a sand pile is a complex system and will therefore behave in unpredictable ways. While we cannot predict exactly what will happen and when, we can understand the boundaries of the system and therefore know what is both possible and probable.
We know this from our everyday lives. We don’t know when, where, or how large the next earthquake in California will be, but we know that one will eventually happen. Because an earthquake in California is both possible and probable, local building codes seek to mitigate the risks by utilizing specific architectural designs and structural reinforcements. When we sit at the beach on any given day, we cannot possibly predict the form of every crashing wave and the shape of every turbulent eddy in the water’s retreat, but we can easily “predict” a range for the size of the waves that will wash in over the next hour. “Between 1 and 4 feet, but most likely 2,” we might guess based on the waves we’ve seen, and then we might let our children play in the surf, confident that an 18 foot wave won’t suddenly arrive and ruin the day.
Although events within complex systems are unpredictable in their timing and details, we can still (1) understand that they’ll happen, (2) know that when stresses are building the events become more likely (and larger), and (3) recognize the rough boundaries of the system.
The Master Resource
When oil first began to be used for industrial purposes at the turn of the last century, world population stood at 1.1 billion and sailing ships still plied the waters alongside coal steamers. Since then, world population has expanded more than 4 times, the