A language defined by David Bourland to reduce Semantic Noise.

Defined as an English language derivative that eliminates use of the verb "to be" in any form (such as "am", "is", "was", "are", "were", "be", and "been")

  • substituting "it seems to me" is maybe a first step, but that's often just a sneaky way of saying the same thing. But it's still some improvement

  • a big part of the danger is the "UniversalIty" of any Is A statement. So defining the conditions under which something "is" true can be helpful.

  • another transform is to use Operationalism, and speak in terms of actions performed by actors


Another source of Semantic Noise, I think, is making statements about causality. When we're talking about Real World systems,

  • testing/proving causality is pretty tricky, from an epistemology standpoint

  • there are usually multiple causes (or "factors") associated with an outcome, and it's pretty tricky to define one factor as being "most" important.

I'll red-flag dangerous failures to use EPrime by using the phrase Is A in a sentence, maybe. But probably not: I'm too lazy (hah, a self-referential failure, I is a lazy person).

It would be cool to translate (other people's) "noisy" writings into EPrime, but this often isn't possible, because you don't know what their signal is. At best you can red-flag Semantic Noise, and value it accordingly. The cool software in Brin's Earth does this...

Robert Anton Wilson on EPrime. To understand E-Prime, consider the human brain as a computer. (Note that I did not say the brain “is” a computer.) As the Prime Law of Computers tells us, GARBAGE IN, GARBAGE OUT (GIGO, for short). The wrong software guarantees wrong answers.

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