Cryptocurrencies are complicated.
I know, I know. Some guy on YouTube told you to “hodl” and everything will be just fine. And people who disagree with you are “shitcoiners.”
Yet the hard truth remains. Cryptocurrencies are delicately balanced systems of competing and mutually supporting incentives, weaving in producers, supplies, traders, market makers, monetary theory, human governance, freedom, anonymity, and an impressively deep array of literature and meme-craft.
This doesn’t stop people from assuming the impossible:
- They know how crypto works, thank you very much!
- They know that other people don’t know how crypto works, seriously!
- Everyone who disagrees is a shitcoiner or nocoiner or really just doesn’t get it!
This is another great way to tell that crypto is money. People are not so tribal and emotionally vested in mere currencies (say, cigarettes in prison, or Canadian Dollars).
This conflict between what we know and what we think we know is by no means limited to cryptocurrency. As our world becomes more complex, we become more desperate to simplify. I would call the recent trend towards increased polarization in politics one effect of this cause. Issues become more complex, and those who wish to have influence must simplify.
Simplifying is terrific. We should have more of it. If someone is not capable of simplifying something, they don’t really understand it, and you shouldn’t take their word for it or buy their ICO.
Increasingly we are running into problems that are beyond the human capacity to rationally solve. In isolation this isn’t so bad. The problem begins when we refuse to admit this to ourselves — stubbornly insisting that “we” know the solution, that “they” don’t, and that if only we were able to have our way it would all be just and good.
An example of this is the religious appeals to “science” in today’s political arena, which are actually appeals to human scientists. If someone is telling you the science is settled, what you should understand is they have something to gain from other people believing the science is settled. Actually settled science does not involve debate or political advantage.
We see this from defenders of Bitcoin Core’s 1.000MB blocksize, advocates that the solution to global warming is higher taxes, and people who believe that Australia is the final model for gun control but Switzerland does not exist.
And we see this from both sides. As you know I am quite openly pro-freedom, pro-free-markets, and against all forms of coercive control. The hardest part about maintaining this position is understanding you are vulnerable to the same hubristic misunderstandings.
I think the only true experts in complicated empirical systems like cryptocurrencies are those who lose the most when they are wrong. This disqualifies, for example, just about every investment analyst you see on television. It supremely qualifies successful bitcoin miners, who are risking millions and billions of dollars with every decision. This “skin in the game” argument has been experiencing a resurgence in popularity, well articulated by Nassim Taleb, after falling off the human radar since the advent of universal central banking some 115 years ago.
This is why hard forks are crucial.
There is not a possible rationalist position to correctly pontificate on the best direction for a cryptocurrency. The best direction, for a myriad of possible reasons, will not necessarily win in the real world of human competition and incentives and competing self interest.
It gets messy in the non-digital arena, where one cannot hard fork so easily amid physical obstacles like the Berlin Wall, imperial occupiers, or even the USA’s modern “exit tax” Berlin Wall. Agreement is forced until it is violently overturned.
This is the real revolutionary potential of cryptocurrencies. Disagreements may be empirically resolved without the requirement of violence.
My favorite examples of the Empirical vs the Rational
Example One — The Artillery Problem
Say you wish to fire a projectile. What’s the best angle to shoot?
We know this almost intuitively, and even moreso after learning (highly rational) Euclidean geometry and Newtonian physics.
OBVIOUSLY it’s 45 degrees!!!!111
Unless, of course, you are firing a projectile on a planet with an atmosphere. Once you account for wind resistance, closer to 40 degrees tends to be better. Then again, this is a function of the speed of the projectile, the wind conditions…so many other variables. You can model them with almost astounding accuracy and get a pretty good mathematical formula to tell you right where your projectile will land.
Alternatively, you could simply practice in the real world until you know what you are doing. Nelson’s gunners at Trafalgar were excellent shots, because they trained thousands of times before and had a good idea how inputs affected outputs in the real world. Not because they were chiseling equations on the quarterdeck and ratcheting just so.
Example Two — The Two-Body Problem
Newton was the first to describe gravity and how its universal attractive force shapes the orbits of planets. It’s possible to exactly define how two bodies of defined mass and at a defined distance apart will behave:
What splendid equations! Simply pop in your numbers and voila, you may describe reality*
But what happens if you add a third body?
You get a new set of differential equations that do not resolve into an exact mathematical formula. You must brute force this problem to get a “correct enough” answer.
We are able to do this with computers, solving for ever higher levels of accuracy, to the point where our empirical understanding of orbital mechanics allows us to do some goddamned miraculous things with a remarkable level of accuracy and confidence.
But the accuracy is only possible as we are able to specify the exact limits of what we know and do not know.
Example Three — War
Even the simplified versions of this human activity, like chess, remain almost infinitely complex. The best chess players are experts, to be sure, but more through practice and experience than pure theory.
Deep Blue and Alpha Go were not perfectly programmed by humans to have a theoretical edge over any opponent. They were run through thousands and thousands of actual games, an iterative experimental “study” that is more analagous to human “practice” than machine “learning.”
Never, never, never believe any war will be smooth and easy, or that anyone who embarks on the strange voyage can measure the tides and hurricanes he will encounter. The statesman who yields to war fever must realise that once the signal is given, he is no longer the master of policy but the slave of unforeseeable and uncontrollable events. Antiquated War Offices, weak, incompetent, or arrogant Commanders, untrustworthy allies, hostile neutrals, malignant Fortune, ugly surprises, awful miscalculations — all take their seats at the Council Board on the morrow of a declaration of war. Always remember, however sure you are that you could easily win, that there would not be a war if the other man did not think he also had a chance.
— Winston Churchill
Today, Machine Learning relies on bots training bots, in a total surrender to the empirical over the theoretical. The best theory today throws up its hands and admits to the importance of iterations.
Cryptocurrencies are empirical. Even though we are surrounded by experts claiming to know things — in an increasingly complex world with more and more interdependent inputs, we must experiment iteratively to truly know. Cryptocurrencies allow violence-resistant iterative empirical experiments through hard forks.
At the time of this post, 1 Bitcoin traded for $9,461 and 1 Bitcoin Cash traded for $1,150 on GDAX.
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