First Puzzle Piece
By and large, the President of the United States can order people to do things, and they will do those things. POTUS is often considered the most powerful person in the world. And yet, the president cannot order a virus to stop replicating. The president cannot order GDP to increase. The president cannot order world peace.
Are there orders the president could give which would result in world peace, or increasing GDP, or the end of a virus? Probably, yes. Any of these could likely even be done with relatively little opportunity cost. Yet no president in history has known which orders will efficiently achieve these objectives. There are probably some people in the world who know which orders would efficiently increase GDP, but the president cannot distinguish them from the millions of people who claim to know (and may even believe it themselves) but are wrong.
Last I heard, Jeff Bezos was the official richest man in the world. He can buy basically anything money can buy. But he can’t buy a cure for cancer. Is there some way he could spend a billion dollars to cure cancer in five years? Probably, yes. But Jeff Bezos does not know how to do that. Even if someone somewhere in the world does know how to turn a billion dollars into a cancer cure in five years, Jeff Bezos cannot distinguish that person from the thousands of other people who claim to know (and may even believe it themselves) but are wrong.
When non-experts cannot distinguish true expertise from noise, money cannot buy expertise. Knowledge cannot be outsourced; we must understand things ourselves.
Second Puzzle Piece
The Haber process combines one molecule of nitrogen with three molecules of hydrogen to produce two molecules of ammonia - useful for fertilizer, explosives, etc. If I feed a few grams of hydrogen and several tons of nitrogen into the Haber process, I’ll get out a few grams of ammonia. No matter how much more nitrogen I pile in - a thousand tons, a million tons, whatever - I will not get more than a few grams of ammonia. If the reaction is limited by the amount of hydrogen, then throwing more nitrogen at it will not make much difference.
In the language of constraints and slackness: ammonia production is constrained by hydrogen, and by nitrogen. When nitrogen is abundant, the nitrogen constraint is slack; adding more nitrogen won’t make much difference. Conversely, since hydrogen is scarce, the hydrogen constraint is taut; adding more hydrogen will make a difference. Hydrogen is the bottleneck.
Likewise in economic production: if a medieval book-maker requires 12 sheep skins and 30 days’ work from a transcriptionist to produce a book, and the book-maker has thousands of transcriptionist-hours available but only 12 sheep, then he can only make one book. Throwing more transcriptionists at the book-maker will not increase the number of books produced; sheep are the bottleneck.
When some inputs become more or less abundant, bottlenecks change. If our book-maker suddenly acquires tens of thousands of sheep skins, then transcriptionists may become the bottleneck to book-production. In general, when one resource becomes abundant, other resources become bottlenecks.
Putting The Pieces Together
If I don’t know how to efficiently turn power into a GDP increase, or money into a cure for cancer, then throwing more power/money at the problem will not make much difference.
King Louis XV of France was one of the richest and most powerful people in the world. He died of smallpox in 1774, the same year that a dairy farmer successfully immunized his wife and children with cowpox. All that money and power could not buy the knowledge of a dairy farmer - the knowledge that cowpox could safely immunize against smallpox. There were thousands of humoral experts, faith healers, eastern spiritualists, and so forth who would claim to offer some protection against smallpox, and King Louis XV could not distinguish the real solution.
As one resource becomes abundant, other resources become bottlenecks. When wealth and power become abundant, anything wealth and power cannot buy become bottlenecks - including knowledge and expertise.
After a certain point, wealth and power cease to be the taut constraints on one’s action space. They just don’t matter that much. Sure, giant yachts are great for social status, and our lizard-brains love politics. The modern economy is happy to provide outlets for disposing of large amounts of wealth and power. But personally, I don’t care that much about giant yachts. I want a cure for aging. I want weekend trips to the moon. I want flying cars and an indestructible body and tiny genetically-engineered dragons. Money and power can’t efficiently buy that; the bottleneck is knowledge.
Based on my own experience and the experience of others I know, I think knowledge starts to become taut rather quickly - I’d say at an annual income level in the low hundred thousands. With that much income, if I knew exactly the experiments or studies to perform to discover a cure for cancer, I could probably make them happen. (Getting regulatory approval is another matter, but I think that would largely handle itself if people knew the solution - there’s a large profit incentive, after all.) Beyond that level, more money mostly just means more ability to spray and pray for solutions - which is not a promising strategy in our high-dimensional world.
So, two years ago I quit my monetarily-lucrative job as a data scientist and have mostly focused on acquiring knowledge since then. I can worry about money if and when I know what to do with it.
A mindset I recommend trying on from time to time, especially for people with $100k+ income: think of money as an abundant resource. Everything money can buy is “cheap”, because money is "cheap". Then the things which are “expensive” are the things which money alone cannot buy - including knowledge and understanding of the world. Life lesson from Disney!Rumplestiltskin: there are things which money cannot buy, therefore it is important to acquire such things and use them for barter and investment. In particular, it’s worth looking for opportunities to acquire knowledge and expertise which can be leveraged for more knowledge and expertise.
Investments In Knowledge
Past a certain point, money and power are no longer the limiting factors for me to get what I want. Knowledge becomes the bottleneck instead. At that point, money and power are no longer particularly relevant measures of my capabilities. Pursuing more “wealth” in the usual sense of the word is no longer a very useful instrumental goal. At that point, the type of “wealth” I really need to pursue is knowledge.
If I want to build long-term knowledge-wealth, then the analogy between money-wealth and knowledge-wealth suggests an interesting question: what does a knowledge “investment” look like? What is a capital asset of knowledge, an investment which pays dividends in more knowledge?
Mapping out the internal workings of a system takes a lot of up-front work. It’s much easier to try random molecules and see if they cure cancer, than to map out all the internal signals and cells and interactions which cause cancer. But the latter is a capital investment: once we’ve nailed down one gear in the model, one signal or one mutation or one cell-state, that informs all of our future tests and model-building. If we find that Y mediates the effect of X on Z, then our future studies of the Y-Z interaction can safely ignore X. On the other hand, if we test a random molecule and find that it doesn’t cure cancer, then that tells us little-to-nothing; that knowledge does not yield dividends.
Of course, gears-level models aren’t the only form of capital investment in knowledge. Most tools of applied math and the sciences consist of general models which we can learn once and then apply in many different contexts. They are general-purpose gears which we can recognize in many systems.
Once I understand the internal details of how e.g. capacitors work, I can apply that knowledge to understand not only electronic circuits, but also charged biological membranes. When I understand the math of microeconomics, I can apply it to optimization problems in AI. When I understand shocks and rarefactions in nonlinear PDEs, I can see them in action at the beach or in traffic. And the “core” topics - calculus, linear algebra, differential equations, big-O analysis, Bayesian probability, optimization, dynamical systems, etc - can be applied all over. General-purpose models are a capital investment in knowledge.
I hope that someday my own research will be on that list. That’s the kind of wealth I’m investing in now.