New Measurements For Complexity And The Meaningful Word Ratio

This is being reposted because more has been added to it.

I have written previously about what a great breakthrough it would be if we could measure complexity. What I mean by measure is to actually put a number on it. As it is now, we express complexity with vague subjective terms such as "more complex than" or "much less complex than".

This has been added to the compound posting on this blog about my information theory, "The Theory Of Complexity".

The reason that we do not naturally measure complexity numerically, as we do time or weight or distance, is that we are more complex than our inanimate surroundings and when we look around us, we are superimposing our own complexity on our less complex surroundings. We have difficulty expressing this complexity as a number because we are literally measuring our own complexity. This is very difficult because, to measure something, we must be able to grasp it's complexity with our own complexity.

I can see how to express the complexity of a number. A number by itself means essentially nothing. Numbers only have real meaning in relation to another number or reference point. My view of the complexity of a number is that of the value of the denominator when the number is expressed as a ratio or fraction. The complexity level of 2 / 5 is 5. A higher number is not necessarily more complex than a lower number because a number like 5 is really 5 / 1, while 26 is really 26 / 1.

But if, as physicists tell us, everything is really numbers, then complexity must somehow be measurable as a number. We just have difficulty seeing it because we are essentially measuring the complexity of ourselves.

Our creation of technology is just imposing our own complexity on our natural environment. I see all examples of technology as being of equal complexity if we add together the internal and external complexity. It may seem that a car is more complex than a cup, but that is only because more of a car's complexity is external. A cup may seem like a very simple device but to fully understand it, and why we would create it, we would have to understand the human body and how it works and why we would need to drink from a cup. All technology is a reflection of our own complexity if we would add it's internal and external complexity together.

My finding is that what it requires is some new and creative ways of measuring. There is a maximum and minimum of complexity between the lower end of inanimate matter and the higher end of our own complexity. If it did exist, we could not measure anything more complex than ourselves.

We can see that humans are more complex than our surrounding universe of inanimate matter. We also know that the more complex something is, relative to it's surroundings, the more likely it is that something will go wrong. So, considering the innate complexity of our surrounding inanimate universe doesn't it make sense that the number of entries in medical textbook, the number of things that could possibly go wrong with the human body, is representative of the difference in complexity between the lower level of inanimate matter and the higher level of human beings?

The reason that people are different from one another is random mutations caused by radiation and other factors in the surrounding natural environment. But humans are clearly much more the same than they are different. So doesn't it make sense that the sameness of humans divided by the differences between humans would equal the higher complexity of humans divided by the lower complexity of inanimate matter?

The fact that humans can recognize each other is a reflection of the fact that our brains must be more complex than our bodies. If our bodies and brains were of equal complexity then we would be able to tell another human being, but not to differentiate one from another.

So this then gives us the measurement perspective that the ratio of the complexity of our bodies, divided by the lesser complexity of our inanimate surroundings, must be equal to the ratio of the complexity of our brains, divided by the lesser complexity of our bodies, which makes it possible for us to recognize each other.

We cannot always recognize everyone from everyone else. Some people look so alike as to be virtually indistinguishable. But this reveals another interesting equality. The number of possible entries in a medical textbook, the total number of things that can go wrong with the body because it is of a higher level of complexity than it's inanimate surroundings, is essentially equal to the total number of different people that we can recognize, with the recognition not being limited to sight.

PLANTS, COMPLEXITY AND, DIET

What about the number of plants required in the soil to keep humans in optimum health? This includes those used as feed for livestock or seafood. My theory is that while humans are more complex than our inanimate surroundings, plants are not. Plants are actually more intricate than the surrounding natural environment, meaning complexity per mass, but are not overall more complex.

But food is what we use to maintain our higher level of complexity against the downward pull of our less-complex inanimate surroundings, our lives and health, being surrounded by the lower complexity of the inanimate universe. This lower level of complexity continuously tries to pull us back down to it's level, and eventually succeeds when we die, and partially succeeds when we get sick or injured. We use, either directly or indirectly through meat, plants to sustain us. But since any one plant is no more complex than our inanimate surroundings, no single plant can really provide a balanced diet for us.

We could thus say then that the number of plants required to provide an optimum diet is equal to how many times more complex we are than our surrounding inanimate environment.

Remember that we see how plants are more intricate than, but not more complex than, the surrounding inanimate universe in that they do not require free will. Free will, such as humans and animals have, only makes sense if the living thing can make decisions. We can only make decisions if we could possibly be wrong. We could only possibly make wrong decisions if we were more complex than our surroundings and there was not enough information in those surroundings to match our own complexity with which we see those surroundings. A living thing can never be wrong about anything if it is no more complex than it's inanimate surroundings.

So we can add this measurement perspective to the perspective above, about the medical textbook and the ability to recognize each other. The number of different plants that we need for an optimum diet, including those eaten indirectly as meat, is equal to the ratio of our complexity over the complexity of our inanimate surroundings. This has never been pointed out before.

THE COMPLEXITY OF SOCIETY

As we impose our own complexity on the surrounding inanimate matter, our society grows more complex. Since this complexity of society must be somewhere in between the base level of the complexity of inanimate matter and our own complexity, that means that it must be measurable.
One way to measure the complexity of society is by the total number of definable job descriptions. Since each job description is a numerator of 1 in a ratio over a denominator, that means that the value of the denominator is a quantification of the complexity of society.

Distance is information also and we can also measure the complexity of society by the total amount of traveling that is done. But we can see that the number of job descriptions and the total distance traveled are interchangeable, different functions of the same thing. When humans settled from being nomadic hunter-gatherers into farming at static settlements, the total distance traveled decreased but the number of definable job descriptions, facilitated by the division of labor, increased.

Suppose that there was an imaginary day in the future when we will know all that we can possibly know, we can call it K-Day. Consider that to express something in numbers we have to completely understand it, we describe with words what we do not completely understand. This means that, the more knowledge we gain and the closer we move toward the day that we know all that we can possibly know, the higher the proportion of our information we will express in numbers, rather than in words.

It indeed seems that we are expressing more information in numbers than in days past and the total proportion of knowledge expressed in numbers should show us how we are progressing toward K-Day.

I am fascinated by the idea of quantifying complexity, actually putting a number on it, and all of the benefits that would bring. We can put a number on complexity but we cannot measure it with a ruler or a scale. It requires some new and creative ways of measuring.

THE MEANINGFUL WORD RATIO

Our alphabet generally has a letter representing each fundamental sound of speech that humans use. The total number of these fundamental sounds of speech is, of course, related to our complexity. Aside from the letters of the alphabet we also use numbers, structured from fundamental digits that function in a way similar to that of letters.

But the difference between letters and numbers is that, while all combinations of digits forms a meaningful number, only a certain proportion of letter combinations forms meaningful words. The number of digits that we use to express numbers, ten, is simply a reflection of ancient people counting on their ten fingers and is not a reflection of our complexity. In any case, the number base that we use would not affect the basic operation of mathematics.

Consider the following potential single-syllable words that possibly could be words. but do not yet have a meaning assigned to them, possibly excluding names:

Kilp
Wun
Bant
Dop

I find that this proportion tells us a lot about where we stand in relation to knowledge. We could call is the "Meaningful Word Ratio".

We have a certain complexity level that is higher than that of our inanimate surrounding universe. My view of all technology is that it is imposing our complexity on that of our inanimate surroundings. Being limited, we cannot ever know everything but there is a potential of what we could know. Since we are always learning new things we can be sure that we have not yet reached that potential which does, of course, depend on our complexity, and this complexity of ours is the same complexity level which governs the number of fundamental speech sounds that we use.

The conclusion that I come to about this is that, if we could perfectly impose our complexity on our surroundings in creating technology, and could know all that we could possibly know, we would have to coin new words that would make a meaningful word out of all possible letter combinations, following the rules of wording such as vowels and consonants and dipthings, without lengthening the average length of a word because that brings about more possible letter combinations.

This does not apply to names became names are a function of words, being secondary to words. We use words to describe patterns because there is not enough information in the universe for everything to be completely different from everything else. We use words for the resulting patterns such as: house, tree, cloud, car, planet and, star because there are many of these patterns, not just one of each.

But yet different examples of such patterns are not identical to one another, and we can thus differentiate between examples of the same pattern and use names to describe this differentiation. There are a number of planets that we can differentiate, as well as different species of trees and of makes and models of cars so we use names to define these differentiations although they fall into the same pattern as described by a word.

Numbers are innate to the inanimate universe around us. Everything is really numbers being manifested. But words are our creation and their usefulness results from our scale and our perspective on the universe. if we were much larger in scale, or smaller, or our senses were different, we would use the same numbers but our words would have different meanings.

What I find so interesting about expressing our present knowledge and technology as a ratio of what our knowledge and technology could, given our complexity level, possibly be is that our use of words themselves are a reflection of the fact that our knowledge is incomplete, or has not reached it's full potential.

Numbers are more precise than words. But, for that very reason, we have to understand everything about something, the calendar for example, to be able to describe it with numbers. We have to know something to be able to express with words, but if we knew everything about it we could express it with the more-accurate numbers instead. In other words, numbers are for what we completely understand and words are for what we partially understand.

That means, once again, that we can estimate where we stand with knowledge, what we know now in comparison to what we could potentially know, by scanning a vast number of documents and counting the numbers relative to words, and than taking comparable measurements on older sets of documents.