The Simplicity of Complexity That Orders the Chaos

In hindsight, I view this post on the illusion of complexity the most important that I've written, primarily because it crystallized my thinking on the fractal nature of human cognition (and, more importantly, human action) and did so in a manner that tied it back to so-called "complexity."

NOTE: those links are to three different posts, the first being the most important and the other two putting stakes in the ground re: fractal cognition and complexity, respectively.

I think I can boil things down further.  My working theory is that the true elite (however you label them) are able to shape and control the illusory complexity of society by manipulating a very simple, fractal function that underlies how human beings make decisions and, therefore, act. I've described the base fractal function qualitatively numerous times in the past, including in all of the linked-to posts, above.  To understand how the same simple fractal function can lead to widely different results, see here.  You manipulate the human fractal through the social institutions that set societal values (i.e., the coefficients in the equation).  The founders of Neoliberalism understood this and set out to control those institutions.  And they succeeded.

My approach to reality forces me to look for the human fractal and its manipulation.  I can't help myself.  For example, whenever I see somebody boil down macro-politics to an either-or, binary choice, I usually confirm both the human fractal and its manipulation.  The fractal is apparent from the urge to drive certainty by limiting the available options to only two.  The manipulation of the function is apparent from the fact that the two options are both ALWAYS dictated by the manipulator.  How is that?  Because the manipulator defines the status quo, and the human fractal naturally creates the opposite of the status quo through the process of normative inversion.  

Another way of getting at what I am trying to say is that if you use their frame, you will lose the game.   An example of this phenomenon may be found here.

What I ultimately hope to accomplish through The Project is to articulate the human fractal in a way that everybody will understand.  Anybody who comes to understand the human fractal can manipulate those who don't and, at the same time, avoid being manipulated.  If EVERYBODY understands the human fractal, NOBODY can manipulate or be manipulated.  My goal is to make sure that everybody gets it.

Change the frame.  Change the game.  Don't get suckered into fighting power with power.  Knowledge trumps.  That's why we're taught to avoid it.

The Fallacy of Fractal Geometry

One thing that I've struggled with for well over a year now is that "fractals" are typically described in terms of geometry and/or probability, while my fractal theory of cognition does not fit easily within that paradigm.

Within the last 24 hours, I realized that even the concepts of the fractal geometry of nature and fractal finance do not truly describe geometry or probability.  Rather, they describe the result of applying a force to an object.  In the case of a coastline's fractal geometry, the force is erosion, and the object is rock, soil, etc.  In the case of a stock price's fractal charts, the force is human decision-making, and the object is the stock price.

Viewed through this prism, my fractal theory of cognition is entirely consistent with the broader theory of fractals, which suggests that we can better understand the fractal geometry of nature by focusing on the physical constants at play, many of which are defined in terms of stress (force) per unit area.  In this sense, fractals are not a "geometry" at all but a very complex derivative of stress (force) and strain (reaction to force).

Fractal Dysfunction

I've recently taken to describing the two most important factions of "the Elites" (note: I did not say "major" factions) as "rationalists" and "realists."  I did not coin these two terms, but I've come to use them in a peculiar way.  In particular, I view "realists," as exemplified by modern realists in the tradition of Carl Schmitt (Hitler's lawyer) and F.A. Hayek (neoliberalism's primary architect) as power addicts, and I view "rationalists," as exemplified by pretty much every other intellectual as enablers of the power-addected realists ("he beats me because he loves me").  Applying the Pareto Principle, I'd argue that 10% of "the Elites" are realists, and almost all of the rest are rationalists.

Interestingly, if you look at the broader adult population, "the Elites" are probably only 10%, leaving almost everybody else-- who I've come to think of as the SSDD (Same Shit, Different Day) crowd.  By the way, I celebrate the SSDD crowd precisely because they are just normal folk trying to get along and enjoy life.  I'd love to be half as happy as the SSDD folks I know, who include the majority of my family.

If my ballpark estimates are correct, that means that no more than 1% of our population dictates how all of us live, which is consistent with economic data.  And I'm sure that we can drill down further and discover that the core power-a-holics that drive society represent only between 0.0001-0.1% of the entire population.

Does that make any sense?  Should the societal equivalent of a desparate heroin addict dictate society's mores and actions?  I don't think so.  The fact that people like me are instictively compelled to fill any perceived power vacuum does not mean that people like me should dictate how everybody else lives.  I am not superior to the SSDD crowd.  Indeed, I'm so far away from the mean that I should be classified as deviant, but people like me are elevated to leadership roles every day.  Unfortunately, the vast majority of people like me view "leadership" as an opportunity to prey upon the rest of society as opposed to an obligation to serve.

Memes: Revolution Through Evolution

As I begin writing my paper in earnest (before I was trying to complete my research and synthesize my findings into a five-page "teaser" for consideration by the judges), I find that the works of the neoliberal thought collective are proving very useful.

When you know the memes that drive the thinking of the people you are trying to convince, it is a simple manner to start with those memes and advance them incrementally to create an "ah-ha!" moment, which marks the creation of a new meme.

So, all I can say is "Thank you, Mr. Hayek!  And you, too, Mr. Friedman!"

Here's an old post (since removed) on how I think about memes in terms of my "fractal cognition" theory:

I have spent the last year studying a variety of topics for the purposes of developing some business ideas that I’ve had.

Initially, I was most interested in developing a new type of media business model, and I wanted to create a fictional universe to support that business model that would appeal to everybody regardless of gender, race, age, religion, national origin, language, class, preferred fictional genre, or preferred media platform. For reasons that I will explain shortly, as I am writing this post, I realized that what I am trying to develop with this new business model is a meme-engine. My initial studies focused on myth (e.g., Joseph Campbell), all major Eastern and Western religions, philosophy, psychology/cognitive science and neuroscience. I was also drawn into studying political economy, today referred to as “economics,” and the major forms of political thought for guiding economic policy (i.e., capitalism, socialism, communism and libertarianism).

Most recently, I have been focused on writing a book about using intellectual property to set competitive strategy, which has led me to the concept of “memes,” which was first introduced by Richard Dawkins in his 1976 book The Selfish Gene. Just as with my new media business model, I want the book to reach the widest possible audience. To that end, I have been speaking with friends who have published books on IP to get their thoughts on what works and what doesn’t. I’ve also surveyed the landscape of IP-related books to confirm that what I have to say is new and different, which it is. I already believe that what I have to say is important. The problem is that having something important to say does not mean that it will be accepted, and, if what you have to say appears to be too new or too different, it likely won’t be.

In the Selfish Gene, Dawkins posited that the basic concepts of Darwinism are something that apply not only to the evolution of the human organism (e.g., by acting on genes) but to the evolution of human cultures. Dawkins identified the meme as the unit of replication (or replicator) for cultural evolution, just as the gene is the replicator for human evolution. Dawkins argued that “[j]ust as genes propagate themselves in the gene pool by leaping from body to body via sperms or eggs, so memes propagate themselves in the meme pool by leaping from brain to brain via process which, in the broad sense, can be called imitation . . . if the [meme] catches on, it can be said to propagate itself, spreading from brain to brain.”

It turns out that I am trying to construct a meme that will sell my book (and me), so I’ve been studying up on memes for the last couple of days. After several iterations over the last six months, I have determined the meta-message of the book, its basic structure and outline for the book and how I will present my ideas. The one thing that I am struggling with right now is how best to construct the meta-message in a way that will catch on. On the one hand, there is an existing meme that blinds people to the true competitive value of IP, and I can probably extend that meme to deliver my meta-message. On the other hand, the existing meme is so self-limiting that it may be best to scrap it and provide a new one, but will it catch on?

To be clear, I do not believe in memes as defined by Dawkins or his successors (e.g., Susan Blackmore or Robert Aunger), just as I do not believe in the reflexivity of markets as proposed by George Soros or the fractal nature of markets as described by Mandelbrot. While I believe that all three concepts are useful and helpful in understanding the RESULTS of human behavior, I think they miss the mark because they do not help in understanding the underlying behavior. That is, the concept of the meme is pitched at too high a level of abstraction to be useful in predicting which ideas will become memes.

Luckily, my study of cognitive science and neuroscience provides the answer, or at least I think it does. I have come to view human beings as “expectation-engines” that are constantly trying to predict the future based on their understanding of the present. At the physical level (or the physical layer of abstraction), the brain contains systems that essentially act as a comparator that employs positive feedback to create hysteresis (i.e., a kind of Schmitt trigger). This comparator compares what is observed to what is expected and outputs a signal that everything is either okay or not okay. The hysteresis of the comparator essentially provides a guard band, i.e., a range of outcomes that are “close enough” to be considered within expectations. If everything is not okay, the matter gets kicked upstairs to the cognitive level (or the cognitive layer of abstraction), which applies a “cognitive bias” as a further guard band; if the cognitive bias convinces the brain that everything is close enough, the physical comparator stops worrying. There are further levels of abstraction, which I have yet to name, but all of them exhibit the same positive feedback mechanism that allows our expectation-engines to believe that everything is going as expected so that we can continue making decisions in the face of uncertainty. The key thing to understand is that the physical comparator is always doing all of the work, that it is the decision maker; what is happening is that more abstract concepts are passed to higher levels of abstraction, which build progressively bigger guard bands (or blinders, if you will) that allow the expectation engine to keep on working. I think that it is this self-replicating comparison function that leads to the fractal nature of markets observed by Mandelbrot, to the reflexivity of markets observed by Soros, and to the memes observed by Dawkins. I have previously identified this as the “fractal nature of human thinking.”

Against this backdrop, I would define a meme as (1) any new idea that (2) catches on quickly (3) because (a) it appears to decrease uncertainty in predicting the future (b) while applying predominantly familiar principles or rules. By defining the term this way, I am trying to explain HOW and WHY a meme replicates itself in terms of how humans actually determine (consciously or otherwise) what to consider and what to ignore in setting expectations for use in predicting the future. Ideas that are so new that they require a new set of principles or rules inherently attack the existing set of expectations and are rejected immediately absent some type of catastrophe that already calls those expectations into question (e.g., without the Great Depression, Keynes’ ideas would not have been adopted to the extent they were). New ideas that seem like old friends, though, they are adopted readily, quickly and widely.

If I can make the case that my meta-message regarding IP decreases uncertainty in business decision-making within the existing paradigm, my meta-message will become a meme.

And Now for Something Completely Different: The Fractal Nature of Human Cognition

Below is repost of a half-baked theory of human-managed systems that I developed in July of 2009.

The basic theory is that human beings are really "expectation machines" that compare what they experience to what they expect and adjust their state accordingly.  The function of the expectation machine includes hysteresis (positive feedback) to maintain the current state unless what is experienced deviates from expectations by too far a margin.  In cognitive science and behavioral economics, this hysteresis is known as cognitive bias, of which confirmation bias is but one example. (A good example of how hysteresis is used in electronic systems is the Schmitt Trigger.)  The amount of hysteresis applied to a given decision depends on the level of abstraction/uncertainty involved in the decision.  There's very little hysteresis applied in the decision of whether or not to eat something because that decision is usually based on feeling a physical need to eat something.  There's a LOT of hysteresis applied in speculative endeavors such as "investing" in the secondary bond and equity markets, which can give the impression of manic-depressive market behavior.

The two primary reasons why all mathematical models of economies will fail is: (1) they assume everybody is loaded with the same "expectation function" (e.g., that of utility theory or that of prospect theory) and (2) they model risk without properly considering the hysteresis (a form of memory) induced by uncertainty. 

The fact is, though, that the founders of the neoliberal schools of economics (Chicago and Austrian) knew that their mathematical models were bogus.  Otherwise, they would not have set up think tanks and similar institutions to bombard the public with neoliberal propaganda that shapes people's understanding of reality and, thus, shapes people's expectations.  They knew that economic decisions are not based solely on purely selfish interest but are influenced deeply by societal institutions.  At the end of the day, Mises, Friedman and Hayek were really institutionalist economists who hid behind false mathematical models to mask their neofeudal ideology as the new liberalism.

FYI -- Back in March, attempter (aka Russ) coined the phrase "fractal Walmartization" in a comment over at Naked Capitalism.  I thought it to be an apt description of what he observed, and it is consistent with my half-baked theory.

The Fractal Nature of Human Decision-Making

I spent some of this past weekend diving into George Soros’ The Alchemy of Finance, and I have developed some initial conclusions that I think are interesting.

Before getting into the details of my exploration, I should explain why I’m bothering with Soros at all.

I initially embarked on my present journey by studying the works of philosophers such as Popper, Arendt, and Marx, which led me quickly to other philosophers (e.g., Plato, Hegel, Kant, Smith, Hume, etc.) and economists, which I now call “applied philosophers” (I can’t call them scientists). One of the things that struck me about philosophers is that many of them start out to understand the world only later to shift towards changing the world. They start out by describing the world as they see it (something I viewed as the “descriptive function”) and then turn to prescribing the world as they believe it ought to be (something I viewed as the “prescriptive function”). Marx, a philosopher and applied philosopher rolled into one man, was a perfect example of this tendency. Ayn Rand was another. By comparing what many of these luminaries had to say about the way the world works to empirical evidence to the contrary, I noticed major discrepancies and came to realize that all human beings tend to interpret life rather than experience it, subconsciously applying their “Useful Fictions” and confirmation bias in real time to filter events to shape their understanding of the world.

As the study of philosophy led me to study economics, I ran across Soros’ latest book, which discusses the causes of the current economic upheaval. In that book, he talks about his model of human behavior (he studied under Popper), which was remarkably similar to mine. What I call “Useful Fictions” he calls “Frutiful Fallacies.” What I call the “descriptive function” appeared to be the same as what he calls the “cognitive function.” What I call the “prescriptive function” appeared to be the same as what he calls the “manipulative function.” What he introduced that was different was reflexivity. While reflexivity is similar to confirmation bias, it is actually quite different, at least definitionally. Reflexivity is based on the observation that participants in a market affect the operation of the market and can do so in a manner that makes the market somewhat different than what the participant understood. That is, the cognitive function and the manipulative function act against each other: by successfully manipulating the world, you act to change it into something other than you understand it to be, transforming what was a known known into an unknown known. Markets can be brought to their knees when participants finally recognize that their assumptions were wrong.

I was far more intrigued by the similarity in Soros’ conclusions about human behavior than I was about the causes of the financial crisis. Knowing that somebody who studied under Popper and who has been immensely successful applying his model of human behavior in trading commodities and equities had developed a model of human behavior that was similar to mine encouraged me to continue developing my own model.

So, I delved deeper and deeper into the issue of confirmation bias. Jonah Lehrer’s How We Decide was particularly illuminating of the role that brain chemistry, and especially the dopamine system, plays in decision-making. My interpretation is that the dopamine system does at the physical level what confirmation bias does at the cognitive level. While I think it most likely that most cognitive scientists view the dopamine system as the cause of cognitive bias, I view them as two distinct things despite their striking similarity. The dopamine system essentially engages in real-time pattern-matching that compares actual outcomes to expected outcomes. If everything meets expectations, positive signals are sent. If something is amiss, negative signals are sent. The reason why I believe that cognitive bias arises at a higher level of abstraction is because the possibility of cognitive bias only arises if the dopamine system has alerted the person that something does not quite meet expectations. A strong negative signal would bash through any cognitive bias because, well, SOMETHING IS WRONG!!! The chemical reactions are really strong.

Upon recognizing that confirmation bias is similar to how the dopamine system works but occurs at a different level of abstraction, I struck upon the idea that reflexivity as described by Soros is similar to confirmation bias but occurs at an even higher level of abstraction. Hmmmmm. Isn’t there an example of something that appears similar at every level of detail (i.e., abstraction) and is recursive in nature? Yep, and it is called a fractal.

Once I observed that the dopamine system, confirmation bias and Soros’ reflexivity concept seemed fractal in nature, I started to refresh my understanding of calculus and fractals. Let’s be clear: I don’t believe that any mathematical function can accurately describe human behavior, whether at the micro or micro levels. I do know, however, that “quants” apply fractal algorithms to market data to make buy/sell decisions in the stock market with some success. Could it be that the fractal nature of markets, first observed by Mandelbrot himself, can be explained by the fact that human decision-making itself is fractal in nature? And human decision-making is fractal in nature, could a mathematical model of that fractal at least help identify and agree upon trends that will harm the economy if left unchecked?

While waiting for books to help me bone up my math (I’m still waiting, actually), I decided to dive into Soros’ The Alchemy of Finance in hopes of finding a mathematical expression of the reflexivity function as he saw it. I hoped in vain. In spite of the fact that that the book was first published over twenty years ago, the math explaining it has never been developed. In fact, I believe that the math can never be developed because it is fundamentally flawed.

It turns out that Soros himself offers no mathematical function to support reflexivity, but he does provide examples of how he has detected reflexivity at work in markets and used that fact to make money (lots of money). Others have actually tried to take his narrative description of reflexivity and create a mathematical function, and I think their literal translation of the description into a function was accurate. Unfortunately, the function is wrong because it assumes a constant feedback loop: it assumes that human beings are always consciously comparing reality to expectations. That simply is not the case.

Soros’ examples are based on comparing the price of a commodity to his view of the fundamental value of that commodity over time. By so doing, he can identify a “prevailing bias” and an “underlying trend.” If these two things appear to be “self-reinforcing,” that indicates a boom that can be bought into and sold out of before the inevitable bust. If these two things appear to be “self-correcting,” that indicates a bust that can be shorted.

The problem with Soros’ theory of reflexivity as described is that humans do not constantly consciously compare reality to expectations. The dopamine system does not allow that. The only time that humans check their assumptions is when the dopamine system tells them that something is wrong, and much of the time, the confirmation bias reassures them that everything is alright. The only time that reflexivity comes into play is when social imperatives (i.e., the fact that everybody else seems okay with what is happening) overcome personal concerns that are not tamped down by the cognitive bias. Reflexivity is not a continuous function and cannot be explained by things like stock price. Stock price is, in fact, a derivative of collective decision-making and not a direct indicator of it.

Thus, a better way of expressing of Soros’s reflexivity is as a bias error function that leads to discontinuities (i.e., step functions) in the derivative function that is stock price. And the best way that I can think of to express that function is as a fractal. I don’t expect to succeed in doing that, but I do think that I can make the case that somebody who is actually competent should try to do so. I will explain why later.