The Universal Dynamics of Everything…

Is “Evolution” solely a theory about the emergence of life, or is it a more generalized “Meta-Theory” about “The Emergence of Everything”…


Compressible Dynamics

Over the last 400 years or so Mathematical Physics has become the science that we rely on to explain the behavior of the universe.  Mathematical physics is the ultimate science of the “deterministic/predictable” dynamics of “cause and effect”.

In general, the Science of Physics likes to believe that all dynamics, all natural behavior, can be explained mathematically; and consequently physicists like to build “mathematical models” of (cause and effect in) the real world.  Sometimes these models are unbelievably concise, and can be expressed as a neat linear differential equation, and when this happens we confidently call the model a “Deterministic”, “Law of Physics”.

It is precisely because of these so-called “hard and fast scientific laws” that physicists are wont to describe their science as the hardest of “hard science”.  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 soft sciences are condemned to deal with our everyday world which is full of noise — because virtually everything in our everyday world 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 the nonlinear stuff that can be safely “compressed into the neat linear mathematics of cause and effect”.  In other words; Physics is primarily a science of “linear” dynamics, a science of dynamics “without feedback” (or more realistically a science of dynamics with negligible feedback).  Such dynamics are indeed easily compressible, but our real world is a world that abounds with feedback, a “nonlinear” world full of “incompressible dynamics”.

[Note: 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.]

Incompressible Dynamics

It could be said that throughout its 400 year history physics has had great difficulty dealing with non “linearizable” dynamics, because these wild dynamics are messy, mathematically unstable, and consequently difficult to predict.

Turbulent systems are the most obvious example.  Turbulent systems are mathematically non-linearizable because they have lots of internal instabilities due to the excessive amount of “energy” in the system.

More recently (in the last 40 years or so) we have started to become more aware of other types of systems that are mathematically non-linearizable.  Complex Adaptive Systems (CAS) are systems whose elements are not completely independent of each other and consequently they can exhibit a lot of internal instability due to the excessive amount of “adaptation” in the system.

The economy is the most obvious example of a CAS.  And so while economists might like to think they can build mathematically models of the economy, this is simply not possible, because the economy is mathematically non-linearizable and full of incompressible dynamics.

In the coming years many more people will begin to understand the difficulty and inherent uncertainty involved in dealing with CAS’s.  As our world becomes ever-more interconnected and co-dependent, more and more systems will become adaptive and complex, and consequently will exhibit incompressible dynamics and unpredictable “emergent behavior”.

And so in the future we will all have to learn to live with uncertainty.  But in case all of this seems overly pessimistic, fear not, for there is another side to CAS.  Complex Adaptive Systems may be unpredictable but they are also massively “Creative”.

The Century of Complexity and Creativity

In Conclusion: Physics tell us that to understand the world we need simply to understand “the dynamics of cause and effect”; but the simple dynamics of cause and effect fail quite miserably when it comes to explaining “Natural Evolution and Emergent Complexity”...

However, understanding evolution is going to turn out to be much more important than anyone might previously have thought.  Because despite what most people might think, evolution is not solely a theory about the emergence of life, but a more “Generalized Meta-Theory” (of which biological evolution is merely a special case).  Evolution is effectively spontaneous and complex creativity in action…

And so although science may have spent the last 400 years honing its understanding of The Linear Dynamics of Cause and Effect, the reality of life in the 21st century is that the really interesting stuff will increasingly result from the “Universal Creative Dynamics” of “Adaptive Integration and Emergent Complexity”…

Matrix of Universal Dynamics - Copyright - Kieran D. Kelly


In Conclusion

The 21st Century will see the rise of the Complex Adaptive System.  Complex Adaptive Systems are systems that are capable (without any external assistance) of self-designing and reinforcing themselves into existence.  This means that, in an evermore interconnected world, the future of the human race is likely to become much more uncertain — but as evolution shows us, uncertainty generates emergent complexity, so

Embrace The Chaos and Harvest the Creativity…

What Drives Deep Creativity?

What Drives Deep Creativity?


Is creativity a “gift” or is it something that is inherent in us all…


Information Creation

Despite what most people might think, evolution is not solely a theory about the emergence of life, but a more “Generalized Meta-Theory” (of which biological evolution is merely a special case).  Evolution is spontaneous and complex creativity in action.  In the broadest possible terms, “Evolution is Information Creation”.

[Note: Everything in the universe is fundamentally an “information structure”.  And a pure information structure is something that is fundamentally incompressible — the concept of which forms the basis of information theory.]

Information is created from information.  Evolution is simply “The Constant Integration of Information”.  Evolution’s progressive complexity is simply Mother Nature creating evermore complex information by “integrating stuff” as she goes along.  This constant integration, this natural creativity, means that “Nature’s complex whole is forever becoming greater than its less complex parts”

Emergent Mind

It would not be unreasonable to say that “The Brain” is the ultimate example (that we know of) of Nature’s spontaneous creativity.  The “Brain” is a “Biological Tool” that has been designed by millions of years of evolution to navigate an external world full of nonlinear feedback and complex incompressible dynamics.

The Brain mirrors Nature in that it is also a complex adaptive system, and it is constantly adapting its own internal “neural” network to the available data and feedback from the external world.  This neural network is, in effect, an “abstract model” – effectively, “a map of what is connected to what”…

So the “Brain” is basically a complex connectivity map, and the “Emergent Mind” simply a reflection of how the brain is wired up.

Consciousness and Intuition

“Consciousness” bubbles up from this emergent mind.  And at its most fundamental, “Emergent Consciousness” is nothing more than the surface representationof a subconscious “library of Instincts” and “laboratory of Intuitions”.

Essentially we can think of instincts as simply hard-corded intuitions, but intuitions themselves are better thought of as soft-coded works in process.

Intuition is the result of a conscious process of compression and subconscious process of integration; a conscious process of figuring out (from feedback) what data is redundant, and a subconscious process of figuring out (from trial and error) how what remains fit together.

Below is a graphical representationMatrix of Cognitive Dynamics[Note:  I address this issue in more detail in my post “What Drives Consciousness and Deep Intuition?”]


Imagination

Intuition is a subconscious process of figuring out what is connected to what.  But the side-effect of trying to figure out how things actually fit together, are thoughts and ideas about “how things could fit together”.

So the mental process of subconscious integration not only drives intuition, it also drives “Imagination”; and so deep intuition offers not only the potential to see complex patterns of information, but also the potential to “Imagine The Unseen”…

Thinking + Feeling

In the simplest of terms, anything that a conscious entity can discern from the external world has the potential to become data for its our own internal model.

It is in the compression and integration of information that “thoughts” begin to emerge  — “thinking” is simply the process of focusing on these thoughts.  When we focus on our own internal thoughts they effectively become our own “internal data”.  But the question arises, “how does one go about evaluating this internal data without any external feedback?”.

Over millions of years, evolution has developed an internal feedback mechanism to evaluate random associations in the brain’s neural network.  “Feelings” are the feedback mechanism for the brain’s “random thoughts”.  Feelings are like “emotional intuition”.  Feelings are the means of determining the “value” of random thoughts.

Deep Creativity

We know that with enough study and practice we can make ourselves into an “expert” in virtually any academic or business domain — but being an expert however is not what it means to be human.

To be human is to be creative.  Our modern society places great store in the value of human reasoning, and has reserved merely a degree of curiosity in the value of human intuition.  Artists however have long employed emotional intuition in “the creative process”.  Emotional intuition is effectively the driver of all human creativity.  Emotional intuition acts as the internal feedback mechanism for identifying the value of “creative integration”, the value of imagination — and true artists have always used this “emotional intelligence” in their creative process.

And so the natural and spontaneous process of subconscious neural integration not only offers the potential for deep cognitive understanding of complexity, but also the potential for “Deep Creativity in Imagining the Complex Unseen”…Matrix of Creative Dynamics


CONCLUSION

So what drives deep creativity?

“What drives Deep Creativity is the Subconscious Integration of a Chaotic Diversity of Ideas”.

And so it is likely that natural creativity is indeed inherent in us all.  By simply allowing our conscious linear minds to explore a wide diversity of thoughts and ideas,

Our Subconscious Nonlinear Minds will gift us

“Deep Creativity for Free!”…

What Drives Consciousness and Deep Intuition?


Did “Consciousness” just appear from nowhere, or is there something about the physical universe that means that consciousness is almost guaranteed to emerge?...


 

PART 1 – CONSCIOUSNESS

 

Over the last 400 years or so Mathematical Physics has become the science that we rely on to explain the behavior of the universe.  Mathematical physics is the ultimate science of deterministic cause and effect.  But although physics is good at explaining the obvious dynamics of  cause and effect, it turns out that it fails quite miserably when it comes to explaining the not-so-obvious dynamics of “Natural Evolution and Emergent Complexity”

Compressible Linear Dynamics

In general the science of physics likes to believe that all natural behavior can be explained mathematically, and consequently physicists like to build “mathematical models” of (cause and effect in) the real world.  Sometimes these models are unbelievably concise, and can be compressed into a single neat equation, and when this happens we confidently call the model a “Deterministic” “Law of Physics”.  However in reality the universe has a range of behavior, from simple to complex, and so unsurprisingly many behaviors are not so easily compressed.

Incompressible Nonlinear Dynamics

The reality is that physics is, in a sense, primarily a science of “linear” dynamics, a science of dynamics “without feedback”.  Such dynamics are indeed easily compressible, but our real world is a world that abounds with feedback, a “nonlinear” world full of “incompressible dynamics”.

Nature is the ultimate example of a complex “adaptive” system full of incompressible dynamics.  And while there are many systems within Nature which exhibit obvious cause and effect; most of Nature’s behavior is however much more nuanced, and consequently much more difficult to predict.

Complex adaptive systems do not follow strict cause and effect “rules” but instead they have a lot of emergent “associations”.  So unlike simple linear dynamics we cannot learn about complex nonlinear dynamics by simply discerning the “mathematical rules”.  To truly understand complex nonlinear systems we need a different type of model.

[Note: 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.]

A Different Type of Model

The “Brain” is a “Biological Tool” that has been designed by millions of years of evolution to navigate an external world full of complex nonlinear dynamics.

The Brain mirrors Nature in that it is also a complex adaptive system, and it is constantly adapting its own internal “neural” network to the available data from the external world.  This neural network is, in effect, an “abstract model” – effectively, “a map of what is connected to what”…

[Note: In the real world, we use such abstract models all the time.  A map of the London Underground is a perfect example.  

Model/Map of the London Underground Transport System

This nonlinear map is obviously not an exact representation of locations in physical space, but it is nonetheless a good enough model, to give us a working understanding of the fundamental structure of the underground network.]

So the “Brain” is basically a complex connectivity map, and the “Emergent Mind” simply a reflection of how the brain is wired up.

“Consciousness” bubbles up from this emergent mind.  And at its most fundamental, “Emergent Consciousness” is nothing more than the surface representationof a subconscious “Library of Instincts” and “Laboratory of Intuitions”…

  

PART 2 – DEEP INTUITION

 

So emergent consciousness is simply the “surfacing” of a biological process of “abstract modeling and pattern recognition”.  But over many millions of years however, “The Conscious Mind” has developed way beyond mere pattern recognition.  This development is most obvious in modern humans.  Over long periods of time Mankind slowly turned recognizable patterns of cause and effect into technology and engineering by a gradual process of trial and error.  And in the last 400 years or so, human consciousness took things a step further by actually teasing out the underlying mathematics that governs the linear dynamics of cause and effect.  But despite all this incredible evolution of conscious and rational linear thinking, we can still struggle badly when it comes to dealing with “the dynamics of feedback and nonlinear complexity”…

Fast Nonlinear Thinking

The Brain has been designed to deal with a nonlinear world, and complex nonlinear pattern recognition is actually it speciality.  The subconscious mind is a library of instincts, and a laboratory of intuitions.  Essentially we can think of instincts as simply hard-corded intuitions, but intuitions themselves are better thought of as soft-coded works in progress…

Some time ago Daniel Kahneman wrote a book called “Thinking, Fast and Slow” in which he basically suggested that we cannot rely on our fast thinking intuition; that generally speaking while our intuition works well when dealing with simplicity, it tend to lets us down when dealing with even the smallest amount of complexity.

This however need not always be the case.  The reality is that, in an ever more complex interconnected world, our fast “nonlinear” thinking can be a much more valuable, and “insightful”, tool than our slow “linear” thinking – but in order for this to be so, we do need to train it correctly…

Integration for Free

In his book “Bounce” Matthew Syed argues that “Talent” is not God-given, but must be worked at — the ultimate result of many long hours of practice.  Virtually anyone who is any good at anything will recognize the truth in these words.  But how exactly does practice make perfect?…

Think about what is involved in learning to play tennis to very high level.  Bad tennis players essentially play every shot more or less the same way; the forehand is almost the same shot as the backhand, even the serve is essentially just racket meets ball.   People who play tennis well however, have learned to separate, or differentiate, one stroke from another; they have fine-tuned the mechanics of each individual stroke from hours and hours of practice and “evaluated feedback”.

Strangely enough though, despite this constant focus on training the mechanics of each unique stroke, nobody ever seems to train the transition from one stroke to another — that somehow just seems to come naturally over time.  It seems that the co-training of a diversity of different strokes means that the integration comes for free…

In truth however while “practice focused on feedback” may consolidate the technique of each individual stroke, it is only through “competitive practice” that these finely-tuned strokes are ultimately combined into a single integrated style of play.  It is this competitive practice, this necessary “integration” (of a repertoire of differently trained strokes) that ultimately makes “the whole greater than the sum of its parts”

Differentiate + Integrate

Learning to play tennis (or anything else for that matter) is simply a process of work and play, of training and application, of differentiation and integration, repeated over and over again.  In a similar vein, “Intuition” can be thought of as a nonlinear map, built from the bottom-up by the constant interplay of conscious differentiation and subconscious integration.

[Note:   In general, as humans, we learn to model the world by trial and error (although trial and evaluation of feedback is probably a more accurate, if clumsier, representation).  The brain makes sense of the world, the same way a child makes sense of a jigsaw puzzle.   A child will separate out all the edge pieces, separate out all the sky pieces, separate out all the castle pieces etc, etc, and then try to fit them all together.]

The brain carries out the conscious process of differentiation when awake and deeply focused and the subconscious process of integration when asleep and deeply relaxed.  During sleep the subconscious mind is effectively trying its best to compress and integrate the diversity of information it has learnt into a single “Coherent Whole”.

[Note:  The information can only be compressed to its maximum compression but no more — this is the basic idea behind something called “information entropy”].

Language is probably the most obvious example of the nonlinear emergence of integrated feedback.  A child does not learn to speak by learning the linear rules; it is only with much practice, attention to feedback, and deep sleep, that nonlinear language ultimately bubbles up to the surface…

This nonlinear learning, this subconscious integration, bubbling up to the surface is the same process that drives our “Intuitive Pattern Recognition”.  And so if the premise of Matthew Syed’s argument (that only “evaluated” practice makes perfect) can be extended to the nonlinear mind, then any lack of “deep pattern recognition” is simply a lack of subconscious integration, which itself results from a lack of both conscious differentiation and conscious awareness of feedback…

Integration + Inspiration

It is often said about great discoveries that, “chance favors the prepared mind”, and so it is with deep pattern recognition.

Through the subconscious integration of a diversity of information a fully formed coherent idea can suddenly emerge into consciousness as if by a random thought.  But this is not really a random thought.  This “information structure” has probably been forming in the subconscious mind for a very long time indeed — before ultimately surfacing into consciousness in what appears to be a moment of “eureka” inspiration.

So although such spontaneous insights (about “how things fit together” ) can seem as if it they come out of nowhere; they are in fact simply the result of the nonlinear integration of a diversity of information which ultimately surface in moments of “Deep Intuition”.

Below is a graphical representation of the interplay of diversity and selection (by compression + reinforcement)Matrix of Cognitive Dynamics


CONCLUSION

Both “Consciousness” and “Deep Intuition” are obviously merely different levels of cognition and “Awareness”, but what differentiates them is what drives them…

“What Drives Consciousness is the Subconscious Compression and Reinforcement of Data”.

But what drives deep intuition is slightly more nuanced.

“What Drives Deep Intuition is the Subconscious Integration of Chaotic Diversity of Information”.

And consequently just as the integrated game is a free by-product of the co-training of a diversity of different tennis strokes, so too when we co-train our conscious linear minds on a wide diversity of data,

Our Subconscious Nonlinear Minds will often provide

Deep Intuition for Free!”…