Objective Inference

Efficient Problem Solving With Object Language

Original post: http://www.derekpage.net/article/serial-thought.php

There are 2 general ways to solve a problem. The first is to take physical things and fit them together like in a puzzle — to move stuff around somewhat randomly. The metaphor of a jigsaw puzzle can be applied to the way we think, which is where we get the phrase “it fits” when we figure out a solution. When something fits it’s a solution to a problem and when you’ve tried but can’t get it, then give up, you confirm you don’t have a solution. In the same way a puzzler identifies and places tangs into slots in order to solve a jigsaw image, moving parts around somewhat randomly, or perhaps creatively, is in the same respect like trying to fit a nut onto the end of a bolt-screw or trying to move a shelf into a cubbyhole, put a card in a slot, rearrange the flowers pleasantly in your vase, place your new couch in the corner of the room, or hanging a picture with your wife across the room who says “a little to the left.” You accomplish spatial tasks best by judging item placement with your eyes, and thus your eyes determine what fits and what doesn’t. Little if any language is needed. Let’s call this way of solving problems “playing.” The second way of solving problems is language. You think and reason about whatever is on your mind, and with this you explore all possibilities where occasionally you come to a conclusion. Thinking is less advantageous than playing since thoughts can lead to contradictions, and thought is not visible, but it’s less work to think about moving things around than it is to actually do it. For example mechanics make less money than automotive designers because automotive design requires a lot more thought, math, scrutiny, and responsibility than putting things together with one’s hands, but it’s more the creative process which makes sensible, tangible results more difficult to obtain. That’s why degree programs which spend a lot of time in language and math bar thought-intensive industries from primarily physical laborers since these require a greater degree of accuracy. When we speak in metaphors we usually come off more clearly than when we use dry logic to decide what we’re talking about, because metaphors always include real objects which are more clear. If you talk in physical things and verbs moving them around, and people will understand a lot better because they will form a picture in their mind and alter this picture to come up with a solution. When you draw conclusions to your thoughts with a short story people will understand far better than if you wrote it in a formula — the contents of the story are impossible to describe without creating a picture in your mind.

Engineering is an area where complicated language becomes a problem because it’s hard to apply metaphors to describe every nuance. Math usually describes processes in a way not only hard to understand, but more importantly you can’t be inaccurate with math or logic or you’ll fail in its application. The requirement that you pay attention to detail is cumbersome and particular to those who have patience, discipline and intelligence. In contrast a painter applies a semi-haphazard process with their utensils where they apply a process to evaluate their work rather than precede the whole thing with forethought without needing to go through a rigorous process, and they end up with a pleasant result. A counterargument to the prior description of these methods of thinking is the painter’s objective differs from the engineer’s; however, the argument here is the result doesn’t matter. What we seek is to apply the painter’s thinking process to the engineer’s end result — a functional machine. Our problem is that painting doesn’t result in anything functional. A painting doesn’t move, neither does a sculpture usually. An artist attempts to move matter around focusing on the color and shape to produce a pleasant effect, where the final result is usually a predictable size. An engineer constructs with durability, strength, weight and size of the work itself varies widely from one work to another.

Since eliminating intellectual processes in favor of visual ones makes engineering easier, this problem could be mitigated if we were able to create a language whose grammar was restricted to spatiotemporal movement: matter and motion. The object language is nothing new, and has been identified in, for example Bertrand Russel’s Inquiry Into Meaning And Truth. The object language would prevent us from using metaphors, and be spatially sound so we could never arrive at a contradiction. The idea of eliminating metaphors to clarify language dates back to at least Hobbes’ Leviathan — against metaphors for the reason that they’re unclear (thus used as verbal manipulation). Generally, the problem with language is that you cannot see it and you can’t visually determine whether something is correct other than seeing the symbols on paper — but it’s hard to reason with symbols. Additionally the volume of text hides information. You can’t take paper with you, and you have to think in your head to be efficient since it’s more optimal to go over something liberally than to write out every word you think of only to erase it later. In fact it’s probably enough to say that, because thinking requires us to forget words quickly, it’s better than attempting to write down everything. Discourse is inexact and it requires you to trash most of what you’ve said. This must be true — for if thinking were perfect then to solve a problem a person could simply sit in a chair, go from one sentence to the next, and solve any problem in a short period of time. Impossible, as diplomats for example who specialize in speaking, say a lot and rarely solve any of the world’s problems, let alone anything scientific.

Excluding verbs, the truth of a statement is only such when the objects of the sentence can be identified, seen, when they obey the law of coincidence — that two objects can never be in the same place at the same time — and all the metaphors that revolve around building things via thinking seem easier to comprehend because language, which references physically visible objects, can create a picture for us in our mind. We’ll leave out a tangent for that of prima facie non-visible items like atoms and feelings , but their existence still applies to being visible. We can only remember so many words at a single time yet we can see many objects at the same time because we don’t need to remember them to see them — they’re always there, but when we’re thinking of words we must continue to refresh our memories about what we’re thinking about since nobody except those who have great temporary memories (Sigmund Freud is said to have been able to recite entire pages of what he’d read). Writing down what we’re thinking helps but still does not provide us with the visual fitting of the pieces that a mechanic, painter, or hardware technician plays with. Further it’s hard for an employer to gauge the effort of an employee whose job requires a lot of thought, such as a scientist or programmer or engineer, because their tangible work isn’t arrived at through linear processes. They usually need a lot of time to think about it, and it’s not linear since it requires a determined trip to motivate yourself in order to accomplish any work only for a variable, inconsistent level of useful results.

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