Book - Thinking in Systems - Donella Meadows
Everything we think we know about the world is a model. Every word and every language is a model. All maps and statistics, books and databases, equations and computer programs are models. So are the ways I picture the world in my head
our models fall far short of representing the world fully. That is why we make mistakes and why we are regularly surprised. In our heads, we can keep track of only a few variables at one time. We often draw illogical conclusions from accurate assumptions, or logical conclusions from inaccurate assumptions.
]] talks about a similar example saying that the menu is not the food, the images and names of the food are not IT
We became so fascinated with words and concepts that we confuse the world as it is, with the world as it is described (talked about, thought about).
We’re like people eating menus instead of dinners
We confuse happiness with status
We confuse ourselves with our personality, our idea of ourselves, [[
]] (while we are living organisms at one with the World) What is the Self
The map of reality is not reality. Even the best maps are imperfect.
That’s because they are reductions of what they represent. If a map were to represent the territory with perfect fidelity, it would no longer be a reduction and thus would no longer be useful to us.
The mind creates maps of reality in order to understand it, because the only way we can process the complexity of reality is through abstraction. But frequently, we are so reliant on abstraction that we will frequently use an incorrect model simply because we feel any model is preferable to no model.
Investing and probabilities (from Farnam Street)
]] is similarly critical of any model:
A model might show you some risks, but not the risks of using it. Moreover, models are built on a finite set of parameters, while reality affords us infinite sources of risks.
financial events deemed to be 5, or 6, or 7 standard deviations from the norm tend to happen with a certain regularity that nowhere near matches their supposed statistical probability. Financial markets have no biological reality to tie them down: We can say with a useful amount of confidence that an elephant will not wake up as a monkey, but we can’t say anything with absolute confidence in an Extremistan arena.
#### What to do about it?
If one assume that there are no accurate maps of the financial territory, they would have to fall back on much simpler heuristics. (If you assume detailed statistical models of the future will fail you, you don’t use them.)
In short, you would do what Warren Buffett has done with Berkshire Hathaway. Mr. Buffett, to our knowledge, has never used a computer model in his life
The approach requires assuming a future worst case far more severe than the past, but also dictates building an institution with a robust set of backup systems. Extra cash, rather than extra leverage. Taking great pains to make sure the tails can’t kill you. Instead of optimizing to a model, accepting the limits of your clairvoyance.
quantification infuses a false sense of security
Created on: 2020-09-06
Topics: Decision-Making | [[
]] | [[
]] | [[