This is a linkpost for https://linch.substack.com/p/frame-error
In this article you say that you can learn a lot from a single data point, and then give the example of an alien learning a lot about humans by finding a Ford Focus. I don't think this example illustrates your point very well. The reason you can't learn much from a single data point is because you don't know if that data point is average or a big outlier. For example, an alien can learn a lot from a Ford, but can also be majorly misled by a playground space ship. The alien doesn't know whether the artifact is pretend, fake, unusual, outdated, and so can't tell much for certain about humanity, beyond just 'one human made this at one point'.
Seems like this was an inadvertently published draft, but the concept seems roughly like Pauli’s “not even wrong”?
Today I want to explain what I call “frame errors”: a third kind of mistake, distinct from logical fallacies and empirical errors. You can get every fact right and every inference valid, and still be wrong, because your framework for reasoning about the problem is structurally inadequate.
In some sense, the idea is not new. Many other thinkers have pointed out specific instantiations of these mistakes before. However, I coin the “frame error” term to draw attention to the common category across these mistakes, provide tools and worked examples to help readers spot these errors when they occur, and offer advice to help readers understand and identify the meta-errors that might lead them or others to commit frame errors.
This post will go through five common classes of frame errors, with worked examples. I will start with examples that you likely have heard of before, and then end with more novel examples where I was the first person to explicitly point out such errors.
Along the way, I provide conceptual tools to model good thinking, so you can hopefully learn useful rationality and reasoning tips even if you do not buy the frame error construct.
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See more at: https://linch.substack.com/p/frame-error