Why this will be the Century of Complexity…


the-century-of-complexity

ALTHOUGH science may have spent the last 400 years honing its understanding of The Linear Dynamics of Cause and Effect”, the reality of everyday life in the 21st century is that the really interesting stuff is increasingly the result of “The Nonlinear Evolutionary Dynamics of Adaptive Integration and Emergent Complexity”…


Linear and Nonlinear Dynamics

“Physics” is the ultimate science of cause and effect.  Physicists like to describe their science as the hardest of “hard science” because physics can claim to be governed by hard and fast scientific “Laws”.  This of course would seem to imply that many of the so-called “soft sciences” are in some way not quite as elevated, not quite as good.

In truth however we could say that physics is an “easy science”, and the soft sciences are “difficult” because the “laws” of physics only really work in the absence of “noise”, and yet the everyday world of the soft sciences is full of noise because most everything is continually battered and buffeted by “constantly changing feedback” which can generate wild “nonlinear dynamics”.

In reality all dynamics have feedback (and resultant nonlinearity), it is just that some dynamics have much less feedback than others.  Physics is, in a sense, the science of “dynamics with negligible feedback”, the science of “linear dynamics” — or in other words it is the science of the nonlinear stuff that can be safely “compressed” into neat linear differential equations which express neat linear “cause and effect”.

New Paradigm

In the simplest possible terms, linear dynamics are dynamics where the effect is proportional to the cause, and nonlinear dynamics are where the effect can be disproportional to the cause.

Physics, it would be fair to say, has throughout its 400 year history, actively tried to steer clear of messy nonlinear dynamics, and in so doing has actively established a paradigm of linear dynamics; a linear paradigm of cause and effect.

But then, out of the blue, in the latter part of the 20th century, along came both “Chaos Theory” and “Complexity Theory” which between them seemed to hint strongly at a completely different paradigm; a nonlinear paradigm of “Integration and Emergence”…

Chaos Theory and Complexity Theory

Unfortunately however nobody seems to have been paying the proper attention, and so chaos theory and complexity theory, as they stand today, are still a bit of a mishmash of concepts and don’t really have agreed upon definitions.

Chaos Theory, for example, is generally associated with the relatively vague notion of the so-called “Butterfly Effect” (or as the academic community like to say “sensitivity to initial conditions”), but this association has, in my opinion, done more harm than good — for it is misguided, and its misdirection has merely served to mask the true nature of chaos.

Complexity Theory is similarly afflicted, but rather than analyse all the pros and cons of all the various definitions of both Chaos and Complexity, I will instead simply offer my own definitions…

Defining Chaos and Complexity

In my opinion chaos is not primarily characterized by sensitivity to initial conditions; but by emergence of decisions points and the resultant sensitivity to choice.  Chaos is simply “adaptive instability”; it is “unresolved internal adaptation to feedback, surfacing as turbulent diversity on the system level”.  So, in the simplest possible terms, we could say that

“Natural Chaos is Incompressible Adaptive Diversity”…

Complexity is simply the resolution of adaptive instability.  Complexity is the result of the “adaptive  integration of co-emergent diversity”, which ultimately results in “emergent complex systems” that have effectively “organised themselves into existence”.  So, in the simplest possible terms, we could say that

 “Natural Complexity is Self-Integrated Diversity”

Matrix of Universal Dynamics - Copyright - Kieran D. Kelly


Integration for Free

So is any of this important?  Absolutely it is!   We live in a world of nonlinear dynamics, some of it compressible, most of it not.  Physics and Chemistry generally deals with the compressible stuff, but Natural Evolution and Emergent Complexity deals with the rest…

To understand Natural Evolution and Emergent Complexity is to understand how in any system of adaptive entities many diverse things can randomly occur and be reinforced; but furthermore, and much more importantly, it also tells us that

With the co-emergence of diversity,

Complex-Integration comes for Free!…

This “Integration for Free” is evolution’s secret sauce.  Evolution drives the emergence of great diversity, which leads to the natural integration of co-emergent diversity, which drives the next level of emergence.  This constant interplay of integration and emergence means that evolution naturally ratchets-up complexity over time, and consequently “the complex whole is forever becoming greater than the sum of its less complex parts”

Natural Creativity

Some years after its publication, the English philosopher Herbert Spencer summarized Darwin’s theory of evolution as being the “Survival of the Fittest”, but unfortunately this description, although popular, is somewhat misleading.

Evolution is not about the “Survival of the Fittest”; evolution is about the “Integration of the Optimally Adapted” (or more precisely, the optimal integration of optimally adapted diversity).

There is a subtle difference between these two descriptions; the former implies anti-synergistic competition, while the latter implies synergistic collaboration.  When we look at the natural world it is obvious that Nature favors integrated diversity over uniformity.  Mother Nature does not employ an asymmetric “winner takes all” strategy, but prefers a more chaotic, but ultimately more creative, strategy of “mutual reinforcement”…

Accelerated Evolution

More and more in the early part of this 21st century we are being made to realize the creative power of complexity dynamics and its potential for system self-integration and emergence.  In some arenas such as a multicultural society, the economy, technology, the arts, and even our daily lives, self-integration and emergence is a source of great diversity and creativity; but in other areas such as financial markets, terror networks, and the global climate it can be a source of great instability and destruction.

Over the last 400 years cause and effect has told us a lot about the dynamics of simple systems void of feedback, but the dynamics of complex systems alive with feedback is a subject that is becoming increasingly relevant and important to understand.

Essentially natural complexity is, in fact, “self-integrated information”.  All natural complex systems are characterized by the fact that they have “low thermodynamic entropy, but high information entropy”; consequently these systems can be considered to be highly organized but unpredictable nonetheless.

So while most people might think about evolution in terms of “an ecosystem of plants and animals”, the reality is that plants and animal (and the ecosystem itself) are really just “information structures”, and evolution simply keep creating evermore complex information structures (structures that are ever more difficult to mathematically compress).

Evolution is fundamentally a “universal process of change”.  Evolution is not just about biology, but about all “information creation”.  Evolution created us, and we in turn create complex information structures.  In fact it could be reasonably argued that in our ever-more rapidly interconnecting world, we are likely fast approaching a phase transition in human development, a transition to a whole new age ; “An Age of Accelerated Evolution and Information Creation”.  And this coming age will be dominated not by the old linear paradigm of predictable cause and effect, but by a whole new Nonlinear Paradigm of unpredictable “Integration and Emergence”…


Algorithmic Search

The new physics of the 21st century and beyond, will be the physics of self-integrating systems and accelerated evolution.  Understanding this “new physics of evolution” will be essential if we want some control over our ever-increasing inter-connected, co-dependent world.  Artificial Intelligence (AI) is seen by many as a means of dealing with complexity and already AI is being used to get computers to learn, but ultimately this will turn out to be really rather small potatoes; the really big pay-off will come from getting computers to explore.

After studying chaos and complexity for so many years, it strikes me that the universe is not fundamentally (as it so often suggested) purely mathematical, but is more generally “algorithmic”.  The process of evolution is, as Darwin himself more or less suggested, a continual process of the emergence of ever greater complexity; a process which would seem to suggests that Mother Nature is, in fact, ceaselessly executing a form of “Algorithmic Search”, constantly seeking out the most successful combinations of integrated diversity.

If this is indeed the case then it begs the question, “Is what Nature finds simply random, or are some things more likely to be found than others?”  Well, as it turns out, chaos suggests the latter…

The discovery of chaos has alerted us to an algorithmic universe that was previously hidden from our awareness; a nonlinear universe of “complex strange attractors”.  The existence of such algorithmic attractors begs yet another question, “are there some, or even many, hidden gems (or dangers for that matter) in this nonlinear universe that we are as yet unaware of?”

In these early days of the 21st century, we are only just beginning to reach the computational power needed to address this question; and although computational exploration of complex system behavior is still an activity very much in its infancy, it is destined to grow to great importance because, for good or bad, it is safe to say that

The 21st century will be a century that embraces the Creative Power of Natural Evolution and Complexity Dynamics…

Matrix of Emergent Dynamics - Copyright - Kieran D. Kelly

Why it’s Great to be Rich!


Montgomery Burns - 007

Did you ever ask yourself why everyone wants to own property.  Most people will say it is because paying rent is wasted money; but while that might be the reason they tell themselves, the real reason that everyone wants to own property is because property is virtually the only way the average person gets access to leverage.


Access to Leverage

Professional Investors are always seeking low volatility assets that appreciate “reliably”  — especially if they have the ability to leverage that asset.

Throughout most of the 20th century most everyone had witnessed (usually from afar) the wealth growth that could occur through the ownership of property.  Historically property prices do not appreciate very much on a yearly basis, but they do generally rise in line with inflation.  If inflation is 2% and the buyer has access to leverage of 5 to 1, it means the buyer is making 10% per annum on his or her investment.

Thus buying property with leverage provides a good return on an initial investment even in a low inflation environment.  This return, however, gets better, much better, if the asset inflation far outstrips consumer price inflation.  If property is rising at 10% per annum, then the 5 times leveraged return is 50%!  It is easy to see why so many people want in on this action…

Easy Credit

Most people understand that expectations are a major factor in financial markets, and confidence is the major intangible in an economy as a whole.  Policymakers understand that people, and the media in particular, look at the state of financial markets as a guide to the health of the economy.  Therefore, as the conventional thinking goes, if you want to make sure people feel relatively confident about the economy, you probably need to make sure that financial markets don’t tank.

So despite their supposed belief in efficient markets, after the bust of the dot-com boom in 2000, the Fed consciously re-inflated the system by lowering interest rates, which had the side effect of making mortgages very cheap.  Coincidentally, around about the same time, banks were beginning to discover the process of “disintermediation”.

Disintermediation allowed banks to sell off their loan portfolios to third party investors (meaning that whether the loans performed or not became someone else’s problem) and this freed up capital for further loans; ultimately to people who never would have had access to leverage before.

Thus banks’ irresponsible lax extensions of credit, and central banks’ irresponsible lax oversight of the amount of credit in the system served to kick start a positive feedback effect.  Excessive positive feedback in any asset market amplifies market synchronicity which can ultimately cause a herding effect to emerge; turning the so-called “Wisdom of Crowds” into the “Madness of Mobs”

[Note: In engineering terms this is equivalent to  turning a damping force into a driving force; in a sense it is a bit like friction in reverse; heat turning into motion.]

The Transfer of Wealth

Such inefficiency in asset markets are not good for society as a whole for they usually mean that markets start behaving like a ponzi scheme.  Rapidly rising market prices are like a raging forest fire that constantly needs more fuel.  In bubble markets this fuel comes increasingly from the weaker members of society.  In the face of almost daily gains for everyone else, eventually everyone gets sucked in, even those who can’t afford it.

During the property boom, banks fuelled this ponzi scheme by recklessly lending to the ever less creditworthy; which meant that as in all ponzi schemes, the less well off were getting in last, often buying from those who got in first.  Inefficient asset market are generally speaking a very effective way of transferring wealth from the poor to the rich!…

Reflate Once Again

The less well off being allowed to participate in the leveraged game of easy money usually signals the end of yet another positive feedback driven up-cycle.  After the debacle of 2008, the Fed once again, in order to avoid a positive feedback driven down-cycle, decided to reflate; this time not only by dropped interest rates, but also by actively bidding up financial asset markets.

This time around however, although the Fed probably saved the global economy from global collapse, the only people that really benefited were those people who could still afford to own financial assets.

Unfortunately this didn’t include the vast majority of the population, who even if they were not massively in debt, found that they no longer had any access to leverage, and as a result are no longer able to participate in the game of easy money.

Furthermore as if to add insult to injury, the taxpayer ended up picking up the bill for the crash, and in general the rich don’t pay very much in tax…

——

So, all in all it is great to be rich!  While most people only have access to excess leverage at the arse-end of a policy-induced ponzi scheme, the rich have access to leverage all the time.   Some rich people will say that the reason for their ever-increasing wealth is that they are smarter than everyone else, but the truth is, it is so easy to get richer when you are rich, and so hard to get out of the starting blocks for everyone else…

Does Economics Suffer From Physics Envy?


Time is Money - 003


Every year when the Central Bank of Sweden hands out its “Nobel Memorial Prize in Economic Sciences”, there are always snorts of derision and cries of protest that this is “not a real Nobel Prize” and economics is “not a real science”…

The Oxford Dictionary definition of science is “the systematic study of the structure and behaviour of the physical and natural world through observation and experiment”.

Economics is sort of unique among the “social sciences” in that it attempts to apply mathematical rigor to the study of human behaviour.  This would seem to imply that economics is an exact science, like physics or chemistry; which further implies that economists are in the business of discovering “fundamental truths”…

Critics of “economic science” argue that the use of the paraphernalia of physics, like dense mathematical models, is in reality, purely “for show”; a vain attempt to give economics the elevated aura of physics (without unfortunately the same power of prediction). In fact some people would go so far as to say that “economic science” is really about as scientific as astrology and voodoo.

A bit Harsh Maybe !?…


Linear Dynamics

Physicists like to describe their science as the hardest of “hard science” because physics can claim to be governed by hard and fast scientific “Laws”.  This of course would seem to imply that many of the so-called “soft sciences” are in some way not quite as elevated, not quite as good.

In truth however we could say that physics is an “easy science”, and the soft sciences are “difficult” because the “laws” of physics only really work in the absence of “noise”, and yet the everyday world of the soft sciences is full of noise because most everything is continually battered and buffeted by “constantly changing feedback” which can generate wild “nonlinear dynamics”.

In reality all dynamics have feedback (and resultant nonlinearity), it is just that some dynamics have much less feedback than others.  Physics is, in a sense, the science of “dynamics with negligible feedback”, the science of linear dynamics” — or in other words it is the science of the nonlinear stuff that can be safely “compressed” into neat linear differential equations which express neat linear “cause and effect”.

All the mathematical laws of physics are linear approximations of nonlinear behavior.  In fact the reason that these “Laws of Physics” are actually considered to be “Universal Laws” is precisely because the dynamics behind these laws can be linearized (which then allows us to repeat experiments over and over again, with the same initial conditions, and always get the same predictable result).

Nonlinear Dynamics

Ironically, it is our inability to express the dynamics of a system in a linear form that results in us referring to that system’s behavior as being “nonlinear dynamics”.  In the simplest possible terms, linear dynamics are dynamics where the effect is proportional to the cause, and nonlinear dynamics are where the effect is disproportional to the cause.  In any system of any type, the universal causes of nonlinearity are

  1. The inability to damp down constant adaptation causes the emergence of diversity (i.e. deviations from the uniformity of equilibrium).
  2. The inability to damp down positive feedback causes the emergence of bias or “skew” (i.e. some random things can arbitrarily get reinforced).

Economics is highly nonlinear and subject to both incompressible adaptation and incompressible feedback.  This means that there are no, and never will be any “fundamental laws of economics”.  Even  the slightly move away from linearity is akin to moving away from a “law” to a “strong probability”; and economics has moved a long way away from linearity.

Economics is highly nonlinear because economies and economic activity are riddled with adaptation and feedback, which means that even probabilistic predictions can become difficult; but this is not necessarily a bad thing, because this unpredictable nonlinearity can lead to the emergence of unpredictable complexity”…

The Nature of Emergence

In an economy it is innovation that drives adaptation, and it is investment that drives positive reinforcement.

In any nonlinear system, it is hard to know what adaptations are going to occur and which of them will get reinforced through investment; and the more nonlinear the system is, the less amenable it will be to even probabilistic prediction. However this lack of predictability does not mean that we cannot have a “Qualitative Understanding” of the potential behavior of the system.

Both adaptation and positive reinforcement can independently drive emergent behavior, but it is the interplay between the two that determines “the nature of emergence”.  While diverse innovation without positive reinforcement can lead to the emergence of chaos, and reinforcement without diversity to the emergence of a bubble, the right balance between the two will always drive “the emergence of complexity”.

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Aggregated Behaviour

Economies are effectively aggregated behaviour.  Some would argue that, left to its own devices, a society’s aggregate behaviour will self-organise the optimal economic equilibrium; but this is obviously not true, for without laws society’s aggregate behaviour can often disintegrate into chaos.

Okay, you might say, we need laws but we don’t need government nor bureaucratic interference in the economy; but this is not true either.  When it comes to financial matters, in general humans (and banks for that matter) can often behave like complete idiots, displaying a herd-like follow the crowd mentality.

The raison d’être of rational capital markets is that valuable investment funds are allocated to a diverse number of innovative business ideas, thereby generating economic complexity to the benefit of society as a whole.  But with the emergence of herding these funds (and even borrowed funds) are often almost blindly redirected and allocated into one particular area or asset class thereby generating a financial asset bubble to the detriment of society as a whole.

So when it comes to managing the economy, a hands off approach is not always the greatest idea….

Managing an Economy

When it comes to managing an economy, the question that needs to be asked is not what are the driving forces unique to economic systems, but “what the universal forces that drive all complex systems?…”

All complex systems are driven by an interplay of diversity and combination, or in other words, “complexity emerges” as a result of the diversification of uniformity and how this emergent diversity best fits together”.

So in reality, it is not really possible to truly understand economics without understanding complexity, and it is not possible to understand complexity unless we understand the interplay between  order and chaos.

Managing an economy, like managing any other complex system, is an art, or more aptly a talent, like cooking, and like cooking it needs a good chef.  A good chef knows how much of each thing he needs and how long to cook it for (to achieve optimal integration).

Too much reinforcement without diversity of innovation and we get inequality and lock-in. Too much innovation and no reinforcement and we get the chaos of many fragmented ideas (that can quickly form, but just as quickly disappear).

What we need is to ensure that “the demand for investment opportunities is, as much as possible, always in sync with the supply of good ideas”; we need to ensure just the right mixture between innovation and reinforcement to achieve the perfect dish of integrated diversity…

Economics vs. Physics

Both physicists and economists need to realise that economics is indeed a science, just not a linear science; which means it cannot rely on linear mathematics, and thus is not amenable to mathematical prediction.

Economics is a nonlinear science, a “complex system science”, and so although not predictable it is still deterministic, governed by the same universal forces that drive all complex systems.

Economics as a disciple should cease attempting to be like Physics, because although natural systems are predictable, economics systems have vast potential for “unpredictable creativity”, and with the right complexity management we harness this potential, to the benefit of all…