On Randomness

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Randomness is the lack of pattern or predictability in events. That is an individual event cannot be predicted, does not follow a rule or a pattern that would help predetermine its outcome.

Benoît Mandelbrot distinguished several states of randomness. And it is useful to be acquainted with them because they are often mistaken from one another and some inexact comparisons can lead to misconception and misunderstanding and of course deception.

We will explore these various states of Randomness in deeper details in separate chapters

Mild Randomness
Mild Randomness is randomness in a closed environment where external factors have no incidence. Like dice, roulette, card decks or artificially created systems like jars filled with red and black marbles.
An individual outcome cannot be predicted but there are some certainty because some rules are set

  • A classic six face die roll can only yield an integer between 1 and 6.
  • A normal deck of card has 13 cards of each color and only 4 aces.
  • A roulette can only yield an integer from 0 (zero) to 36.
  • A fair coin can only deliver head or tail.

These are convenient to learn about probabilities and get entertained. This randomness is easily mastered and surprises are rare. You are certain that 2 six faced dice will never add up to more than 12, yet streaks of 12 can and do happen. Still, these two dice will add up to 7 more often than to any other possible sum. So betting on 7 will give you an edge.

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This is the randomness that makes casinos rich because regardless of what one person wins, the other will lose it. It is contained within the ranges of what is possible with the dice, cards or the roulette. All that the casinos have to do is to make rules so you get only 97% (or less) of what you bet. The casino gives you 35 times your bet if your number comes out but your number has 1 in 37 chance to come out. Over time the house will win.

Deception (including Self-Delusion) is the only way to escape of the laws of this randomness and life is extremely rich in examples of such deceptions.

Borderline Mild Randomness
The first cousin of Mild Randomness. It applies when the complete population cannot be known but most of it can or when the possibilities are not exactly strictly ruled.

For instance, the range of human sizes are sort of constrained between upper and lower limits but it is impossible to guess how tall an unknown person will be. The 8 feet upper limit is blur and so is the 2 feet lower limit but they are quite safe borders since no person can be 20 feet tall. Or at least none has been found yet. Depending of the population (Netherlands or Mexico) the average can be different but basically the distribution of tall and short people will smoothly follow what we call a normal distribution.

Normal distribution arranges specimens around the average value (drawing a bell curve) and measure how far from the norm specimen are distributed. For example, looking at the goldfish aquarium in a pet store, you will notice that most goldfish are about the same size with some smaller and some bigger and a few a lot smaller and a few a lot bigger. That is normal distribution.

Of course if you pick 3 at random they might not follow the same rules, you may end up with one big and two average size. Normal distribution needs a lot of specimens to work well.

But one can predict to some degree how many specimens can be found in each size range when the population is normally distributed. One can also predict that a specimen picked at random will be within a range of size, for example that an American man will be between 67 and 73 inches (170 – 185cm) tall and be right 68% of the time.

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In the case of fish or trees, or other living organisms, the sizes will obey this law until a giant specimen is discovered. In such case, the giant specimen is usually not considered since it is not representative of the general population. Although such approximation is helpful most of the time, it can have disastrous outcomes when applied where it should not. The main misconception being to disregard what is possible because it is very rare.

Borderline Mild Randomness is studied by insurance companies to offer life policies. They adjust to new life expectancy from time to time and stay in business. Insurance companies do not go bankrupt.

We’ll see later that actually, although these forms of randomness are quite stable (that is over time the events they describe will fall within their boundaries) they can also yield strange results, especially when samples are too small or the terms too short.

Slow Randomness
Slow Randomness is not much a concern.
It encapsulates events that seems stable and predictable but would take too long or necessitate too many trials for us to notice or being affected by their randomness.

The various movements of the Earth through Space are an example. The Earth spins on its axis in 24h and revolves around the sun in 365.25 of these days (these are actually approximations). The Earth is also under forces that tilts its axis back and forth in a 41,000 year cycle and that displace when it is the closest to the sun on a cycle that varies from 19,000 to 26,000 years, depending of other gravitational objects around us, namely the sun and the other planets (those have their own multiple motions as well). Basically, too many things are at play for us predict where our planet will be exactly in 10,000 years. But if we look at it on a smaller scale (a few decades), we can have certainty in extremely fine details as ephemeris can demonstrate.

Another example: dice have tiny manufacturer’s flaws that would eventually change the odds but it would take so many billions rolls to demonstrate it (and to accentuate, change or compensate the flaws by damaging the dice on each roll), that this fact is just an intellectual gimmick. As mentioned before, Slow Randomness is not much of a concern. Casinos destroy dice on a regular basis to avoid cheating, not to elude slow randomness.

Wild Randomness
Wild Randomness is what interests us the most. Wild Randomness is also known as Chaos and Karma. Wild Randomness is subject to the famous Butterfly Effect. Wild Randomness is shit happening. It is the randomness of life. It is the most eluding form of randomness and there is no way to tame it. Read that passage again until it becomes clear to you. There is no way to tame Wild Randomness.

There is no way to tame
Wild Randomness

That means there are domains where predictions are exercises in futility ranging from entertainment to delusion to deception.

Wild randomness is the unpredictability of the weather, of the financial markets, of the economy, of the next chart topping song, of most success in business and of what anything alive will do next.

Many application of science and technology are usually overpowering that randomness so a lot of things have been achieved to control Nature for our benefit and comfort, but there are domains where such control finds its limits. This is when shit happens.

There are, though, many examples where order seems to prime and others where control seems to apply. As in mild randomness, some interesting results can be observed, but for the most part, orders, patterns and control are nothing but delusions and fallacies.

Understanding the true nature of Randomness will help you understand the grounds of these delusions and help you progress in life.

All this may seem vague right now but will be in better explained in separate chapters

Thank you.