Networks -- Smoking, Obesity, and Epidemics

Not all spontaneous orders are good. For example, obesity has been shown to spread through social networks. If you hang out with fat friends, chances are you'll gain a few pounds yourself. Smoking also demonstrates network effects. If a person or people start smoking in a given network, more in the network will start. But if a person or people stop smoking, more in the network will quit. The elements that affect network effects are also interesting. For example, those with more education were more likely to quit if their network peers quit.

Albert-László Barabási also has an editorial in which he discusses network medicine in light of the article on obesity. He points out that these kinds of networks -- disease networks, genetic/regulatory networks, neural networks, and social networks -- all have the same basic architecture, meaning if we understand one network, we understand them all at a fundamental level. He also points out that understanding networks allows us to see connections among things we may not otherwise notice. Diseases can be networked together, and thus understanding one may shed light on another. And as he says "drug side effects are inherently network phenomena." Which is another way of saying there are unintended consequences/spillover effects in network processes. They can be positive, such as the "invisible hand phenomenon" of market economies, or they can be negative, such as drug side effects.

All of which shows that the content of the system matters as much as the architecture. Diseases spread through network effects, with emergent properties, as any epidemiologist will tell you. And there are tipping points. An epidemic is a spontaneous order, but I think we would all, from a human perspective (vs. the germs' perspective) agree it is a perverse one. But tipping points work both ways. Using epidemiology, we can also eliminate diseases. There is a tipping point for wiping out a disease as well.

An Informational Ontology

I do not ascribe to a materialist ontology nor an idealist one, but rather, to an ontology of information. In other words, I take the following from John 1:1 seriously:

en arche hn o logos
"the foundation of all things is information"

Admittedly, this is a definition that comes about in light of information theory -- but if you truly understand both what information is, and all the meanings of logos, you can see that "information" is a good translation of "logos." Certainly a far better choice than "word," which is such a peripheral meaning of logos as to be almost completely inaccurate. When we "Logos," we communicate information one to another, process that information, and pass on that information. All things are information at different levels of complexity -- information processors, which all communicate different kinds of information at different levels. For biological organisms, the vehicle of communication tends to be chemical, though also photons and sound waves. Humans communicate using more complex information-carriers, particularly through grammatical, syntactical language. If we look at the ways to define information -- as a noun, it is that which is without form; as a verb, it is that which gives form to another. Thus, pure information is that which is without form, which gives form.

"The foundation of all things was information, and the information was 1) to the advantage of 2) at, near, by 3) to, towards, with, with regard to (the word translated as "with") God, and God was information."

That is the most literal translation of John 1:1 I can render. The story of the universe is one of foundation on information, and the increasing complexity of that information over time in the universe. Atoms have less complex forms of information than do chemicals and especially chemical cycles and systems. Biology is a set of highly complex chemical systems. The human brain is a highly complex neural system in complex interaction with other humans through complex social systems. That information is communicated through language, which itself must be highly complex in order to communicate most efficiently. One could thus view God as having most complexity of the universe, and thus have all the information. This is how God is both the Alpha (the inform information that gives form at the beginning of the universe) and the Omega (the most complex, most informed).

I suspect this may be too pantheistic for some. Call the all-the-information-at-its-most-complex what you will, then. Call it simply the universe at a future state. But humans are the most informationally dense entities in the universe we know of, and we are highly intelligent and self-aware. If the tendency of the universe is towards greater complexity -- toward increased density of information -- then we can expect more complex, more intelligent, more self-aware beings than ours to evolve. It may or may not be a descendant of ours. But that does not matter. What matters is that we understand this natural evolutionary tendency of the universe as a whole to evolve toward ever-greater complexity.

Complex processes emerge precisely because information is communicated to other entities in the process. In social processes, those entities are agents capable of processing that information and storing it as knowledge, then acting on that knowledge. Much of that knowledge is conscious, some unconscious. Much is tacit. Thus understanding information in the information theoretical sense of the term is important to understanding complex social processes as well as the physical entities that make up those social processes. If we understand that each is in fact made up of different kinds of information, we can bridge the gap among the physical, biological, psychological, and social sciences -- and even bridge those to the arts and humanities.

All the other theories I use in my philosophy, world view, scientific work, and art -- evolutionary theory, game theory, chaos theory, complexity theory, emergence theory, etc. -- explain the ways in which information interacts to create more complex things and how those complex things engage in complex interactions. Information theory is the foundation of all these things. Information is the foundation of all things.

Complex Feedback: Nature-Nurture

Many of us already know that the nature-purture debate is grossly oversimplistic. Still, all data supporting this fact is more than welcome.

We are all born with a set of genes which create our bodies, including our brains, the development of which informs our actions. We are born with instincts, which are genetically encoded. However, the environment also affects gene expression and the emerging structure of our brains' neural nets. This results in reactions to the environment, which change the environment, which in turn affects our brain's gemoetry and our genes' expressions. Etc.

This is, by any stretch of the imagination, a lot of complex interactions.

Nature-only and nurture-only explanations are simple -- indeed, simplistic -- explanations. This is true even though each of the systems involved -- genes and gene regulatory processes, neural networks, and social processes -- are each very complex in their architecture and processes. But let's face it: we are talking about three complex, self-organizing network processes interacting with each other. And we are not even talking about the complex sets and subsets of our social processes, and the interactions of each with the others.

Genetic (inter)actions --> complex bodies, including complex neural network/brain
--> actions and, with other people, interactions --> complex social processes
--> actions and interactions --> neural architecture and (inter)actions
--> genetic (inter)actions --> etc.

Chemical Vapour Deposition Cauliflowers; or, Ignorance and Interpretation in Science

One of the reasons I think there should be a society that brings together all of those who are working in the various sciences involved in understanding emergent orders is that awareness of others' work will 1) reduce the rediscovery of laws/processes that have already been discovered, and 2) reduce the likelihood that there will be less right interpretations, given new information.

I would consider this article on creating cauliflower fractal patterns, summarized here to be an example of both issues. What conclusions would they have drawn if they had been familiar with constructal theory? It is obvious that their evaporation technique is an example of different kinds of flows interacting to create these patterns. Further, power law distributions are not random, so they have a less right interpretation of the data than they could if they had been familiar with the right data. The paper is interesting, but the interpretation coulduse some work.
Certainly part of the problem is that you can't read everything. And rarely does one read outside of one's area of expertise. But complexity science is, I think, necessarily an interdisciplinary science. We are finding these patterns, processes, and strctures everywhere in nature and society. Researchers in all fields need to familiarize themselves with what others are doing, and familiarize themselves with the work being done that is revolutionizing science.

Slow Power Law Avalanches Oscillate

Everyone familiar with complex systems are familiar with the fact that "avalanches" occur in a power law distribution -- few large avalances and many small ones. However, until now, it has been assumed that the avalanches themselves were random. Under the conditions described in the linked paper, under certain conditions, in which slow avalanches are created, the frequency of large and small avalanches actually oscillate. Thus, there is a pattern to the distribution of the power law distribution.

More and more, it seems that processes we thought were essentially random are in fact ordered. But the order is complex, not simple. And it is complex order on complex order -- giving the appearance of randomness.

Chaos Theory and Roulette

If there is anything truly random, surely it is roulette, right? Wrong. It turns out that using chaos theory allows us to discover patterns in roulette -- such pronounced patterns that the odds increase dramatically. Nevertheless, you have to have a lot of equipment available to be able to make the more accurate predictions, so even Mandelbrot's odds wouldn't have been able to have increased under normal conditions.

Does this suggest that there is no such thing as true randomness?

Cliodynamics

The journal Nature has a fascinating piece on cliodynamics -- computer analyses of patterns in history. What I find fascinating is that they end up with exactly the same analysis as I had on the revolution in Egypt. Each each case, we were looking at bubbles and the causes of bubbles. There is a bubble that resulted in the violence/unrest bubble. The bubble of my analysis seems to be the same as the bubble of Peter Turchin's analysis. One gets boom-bust cycles in complex processes when there is positive feedback. Cheap money is a kind of positive feedback. Third party payers, such as we see in health care with insurance, is another. And artificially low interest rates -- meaning, rates below what the market would create -- created the housing bubble that burst in 2008. There was an education bubble in the 1960's that led to the violence of the 1970's. I believe there is an education bubble now, as evidenced by the increasing prices and blooming number of bureaucrats -- and Turchin predicts revolutionary violence in the U.S. of the same kind around 2020. There are more aspects to cliodynamics than education bubble-created violence, and many more I am sure possible. One has to be careful, though, that one does not mistake the model for reality -- these are not accurate predictions, but pattern predictions. These are, nevertheless, very important.