“Using layman’s terms: Use a retaining magnetic field to focus a narrow beam of gravitons. These, in turn, fold space-time consistent with Weyl tensor dynamics until the space-time curvature becomes infinitely large, and you produce a singularity.” – Event Horizon
I tried to explain the budget to my ex-wife, but she couldn’t grasp the gravity of the situation.
Right around the year 2002, I first heard of a geophysicist named Didier Sornette. Sure, you say, with a name like that, he’s French, how smart could he be? Well, let’s get this straight – I still blame the French for cigarettes, Leftism and the metric system, but Sornette is an original and first-rate thinker, even though the actual pronunciation of his name is probably “Dipstick Snort” because the French haven’t in the last 1600 years mastered spelling a word with any relationship to the way it is actually pronounced. In addition to Sornette, the French gave us Sophie Marceau, so there’s something they did right.
Even though Sophie Marceau played a villain, Bond© thought spending time with her was 00heaven.
Sornette is a geophysicist by degree. He initially studied the physics of earthquakes. Earthquakes, Sornette noted, don’t come about due to any single failure, but as a result of the microscope failure under pressure at LOTS of different places that at some point becomes critical. The pressure builds up, and it’s not the first little crack in the rock, but rather the aggregate cracking that eventually releases the stress. It does that all at once.
Sornette thought that he could use math to describe the behavior of rocks, and model it so he could understand earthquakes better. He worked for twenty five years on doing this, and found that there was a mathematical “signal” was present before the earthquake occurred. It wasn’t useful for predicting exactly when the earthquake would occur, but like everybody with a new tool, Sornette looked around and wondered where else it might be applicable.
Sornette looked at the financial system, specifically stock markets. He noticed that stock market crashes looked a lot like earthquakes. And, unlike earthquakes, financial crashes could devastate the world globally. He switched his focus to that, using math to model the financial bubbles that led to the high values that then came crumbling down when the market finally crashed.
In 2001, he decided to take this modelling a step further. What if, he asked (along with fellow researcher Anders Johansen) we try to model not only the financial system, but world population, too?
Okey, I’m betting Anders Johansen-a duesn’t ictuoelly telk leeke-a zees. Prubebly. Bork Bork Bork!
The result was the paper Finite-time singularity in the dynamics of the world population, economic, and financial indices, or FEEnite-a-time-a singuolerity in zee-a dynemeecs ouff zee-a vurld pupuoletiun, icunumeec, und feenuonceel indeeces in Swedish. That’s a really long title that could have been shortened to, Yo, something weird is coming, and I don’t mean your mother. You can find a copy of the paper here (LINK). It shows a May 29, 2018 date, but I don’t think there’s been any changes to it since its initial publication in late 2001. I’ll warn you – there’s a wee bit of math involved.
The paper starts with the statement that for most of the known history of the human race, our growth rate hasn’t been exponential, it’s been far faster than that. It took 1600 years to go from 300 million people in year 0 Anno Domini to 600 million. To get to a billion total only took 204 years. Double to two billion? We did that in 1927. Three billion in 1960, four billion in ’74, five billion in ’87, six billion in ’99, and seven billion in 2011. Now as I write this in 2019? 7.7 billion people. And only forty people are friends with you on Facebook®.
What allowed this population growth? Knowledge. The revolutions in agriculture (the first one, which I wrote about here: Beer, Nuclear Bikinis, and Agriculture: What Made Us Who We Are), industrial, fertilizer, medical, and information have allowed the population growth to accelerate like it has.
Sornette and Johansen studied several data sets. Population was one set, and another was the economic growth rate of the United States, as measured by the stock market. Even though the Dow Jones Industrial Average© (DJIA) didn’t exist before Dow married Jones, several economists have created data on what the data might have looked like. Is that a bit of a guess, like your mother’s weight since there aren’t scales that big? Sure. But, as we will see, it might be close enough.
Math is funny. When you divide something by zero, you get infinity. Several mathematical functions that describe things going to infinity do exist – we call those singularities. The funny thing is that they appear to exist not only mathematically, but in real life as well. They have real properties that we can predict, measure, and see. One popular example of a singularity is the black hole. Some scientist said, “Okay, gravity sucks, like your mom. But what if something had so much gravity that it trapped even light, like your mom?”
That concept blew their minds, but it was there in the math in 1916 when Karl Schwarzschild solved Einstein’s equation and divided by zero. A black hole is a singularity based around gravity – where gravity is so intense that we have no real understanding of what happens inside, like God divided by zero, liked what he saw, and said, “Yeah, this is the ultimate practical joke.” But singularities aren’t limited to stuff that would only interest starship crewmembers. Other singularities regularly occur in physical systems. Earthquakes.
Stock market crashes.
A scientific discussion of gravitation inside a black hole.
This wasn’t the first time someone calculated the date of a singularity based on population. In 1960, the prediction was published in the journal Science that the population singularity would hit on (somewhat tongue and cheekily) Friday, November 13, 2026. Didier and Johansen relooked at the data, and came up with an equation that they felt gave a better fit.
Their date for the singularity? 2052, +/- 10 years.
They then looked at the data (keep in mind, this was in 2001) and modeled the behavior of the DJIA©. What did they find? A singularity in 2053.
That was too close for coincidence. Two different data sets show the same predicted end date?
Thankfully, Sornette and Johansen are wrong, right? They certainly didn’t predict that the DJIA™ would be as high as 27,000 in 2019?
In fact, their prediction (in 2001) was that the Dow would hit 36,000-40,000 by 2020. They did leave some weasel space, noting that, “. . . the extrapolation of this growth closer to the singularity becomes unreliable . . .”
It’s say that they were pretty close, and far closer than I was in the year 2001 when I would have predicted the aggregate stock value of the DJIA© in 2020 would be worth a less than a handful of ramen noodles and ten rounds of .22 ammo. So they were far closer than I was.
One thing Sornette and Johansen noted was that the minor ups and downs would be of less consequence the closer we move to the singularity point. What happens each week is less important than the overall trend, so the data errors associated with “creating” a Dow Jones™ index before there was one probably isn’t too much of an error.
Here’s 100 years of stock market data, now with snarky comment.
Another conclusion of the equations is that population, technology and wealth is intertwined. The number of people that the world can hold is very much tied to technology. When modelling prehistoric population, no fewer than three technological ages – have to be mathematically introduced: hunting, followed by farming, followed by primitive technology are required to accurately model the actual population.
But when these intertwine, does the increased population lead to the technology, or do they feed on each other causing an explosion?
They feed on each other, causing an explosion in technology and population and wealth. More people lead to more wealth. More people leads to more technology to feed people which leads to even more people which produces more wealth which leads to . . . more people. The end dates are similar because the functions of wealth and population are related. You can’t have the super-exponential growth without the interactions. Sornette and Johansen came up with approximately 2050 for the end date. Ray Kurzweil (futurist) predicted the technological singularity would hit around 2045, which is pretty close.
Bill Gates gave up lap dancing and stripping after pulling a hamstring at a bachelor party, and he had to settle for his second love – computers.
But what happens next? What happens if and when the singularity hits? The authors indicate we’re probably in it a transitional phase already – the population growth rate peaked in 1973, and so did the world per capita energy use. Sornette and Johansen came up with some silly ideas of what’s next, but let’s be real: no one can predict what happens after a singularity – dividing by zero changes every rule.
We have no idea what happens inside a black hole.
I know that many of you sense the same thing that I do – we are changing at a pace that is already fast but that seems to accelerate: it’s faster every year. This is the case, and I don’t anticipate that things will slow in the next decade or two. Beyond that? It’s anyone’s guess.
Oh, and if you’re wondering what happened to Didier Sornette? He runs a group called the Financial Crisis Observatory in Zurich, where they try to observe financial budget growth in real time. It’s here (LINK) and worth a few minutes of review.
So, if they’re right, it’s the best time to be in stocks, at least until the singularity occurs, the population collapses and the robots decide that to get rid of their pets . . .
Dow chart from here: (LINK)
