Abstractions Are Real

The real world and it’s behaviors are extraordinarily complex. To theorize and create good explanations necessarily requires some encapsulation of ideas through abstractions. It is possible to understand a phenomena by understanding abstractions and similarly, it is possible to create new explanations by building on top of them.

Knowledge can grow because abstractions are real. It’s not as if every child going to school must learn all underlying knowledge in order to add to it. It’s also not as if explanations are implicitly wrong if all the lower-level behavior is not explained first.

See also:

• Seeking good explanations is error correcting so if abstractions end up being wrong, better ones can be found
• The Beginning of Infinity

Links to this note

• Zeno’s Mistake

  It’s a mistake when confusing an abstract process with a real-world process of the same name. An example from The Beginning of Infinity is the study of decision making. The assumptions that are built into their models are a simplified version of actual real-world decision making because there is not a good explanation of how it works in reality.

• The Internet Is Not Prosthetic

  The internet is not some other thing, separate from life, it is an abstraction that is very real.

• Illusion of Explanatory Depth

  People feel they understand things better than they actually do. This leads to biases and poor decision-making because of overconfidence in their knowledge.

• The Further from the Self, the Less Real it Feels

  The realest thing to anyone is themselves. The further from the self the less real things feel. For example, we know about the stars and distant galaxies but the fly buzzing our ear is more important and “real” as to steal our attention. While we have the power to imagine great things and empathize, direct experience is more important because it involves the “I”. Our wants, needs, and desires exceed the realness of all else.

• Clarity Is One Number

  Making complicated things seem simple involves abstracting over reality in such a way that is clear and actionable. Often times, that means reducing things down to one number going up or down. People are drawn to (fixated even) clarity of a single number going up or down.

• Computers Are Universal Objects

  Computers can be programmed to do anything a model of computation can express. You don’t need to buy a new computer to run Microsoft Word and buy another computer to run Slack. The jump to universality in computers opened up an infinite set of possibilities via software.

• Biologists Don’t Make Good Medical Doctors

  Deeply theoretical fields don’t necessarily translate to highly practical fields. Economists don’t typically do well as investors. Just because biologists know a lot about the inner workings of the human body, doesn’t mean they make great medical doctors.

• Reductionists View High-Level Behavior as Consisting of Lower-Level Behavior Only

  The reductionist view of science is that all high-level behavior consists of the underlying lower-level behavior and should be analyzed into components to fully understand. However, good explanations can be self-contained and sufficient without needing an explanation of every low-level detail. For example, you can have a theory of how water boils that doesn’t need to predict movement of individual atoms.

• Creating Meaning Through Analogy

  One of the most profound findings from Godel’s incompleteness theorem is that meaning can be mapped onto a system that was specifically designed to prevent it. Principia Mathematica, the system Godel was poking at, was designed—amongst other reasons—to solve the paradoxes of set theory and logic with a constrained set of rules. Godel abstracted over the symbolic logic (converting proofs into numbers) to show a self-referencing statement could not only be represented in PM but was also undecidable.

• A Strange Loop Gives Rise to Human Selfhood

  A strange loop is a combination of traits that creates the condition for selfhood. Categories of numerous symbols derive meaning from raw stimuli. Categorization leads to perception rather than reception. Abstractions create reality and high-level behavior no longer consists of lower-level behavior only. The loop reinforces the idea of the ‘self’ and the self feels the most real.

• A Strange Loop and the Illusory Self

  One of the key points of I Am a Strange Loop is how the “I” develops into consciousness. The constant reinforcement (and self-enforcing) of the “I” gives rise to perception, symbols, meaning, and reality. On the other hand, the key point of mindfulness (at least to me) is recognizing the illusory self.

• Abstractions Save Time Working, but Not Learning

  Software abstractions save us time doing work by not having to write programs from lower level building blocks. Programming languages like Python provide an easier way to write general purpose software than say, assembly language.