It all comes together in a perfect storm :: “Keep it Simple”

Three different levels of information processing show a remarkable alignment.
They all are guided by similar principles, which do map and overlap.
Let me briefly summarize them:

Active Inference , a sentient behaviour theory, builds on the free energy principle. FEP implies a coupling between the internal and external states of a system that is symmetric: a system will adapt to its environment, while changing it through action. It follows that individual priors collectively shape macroscopic dynamics, reflecting a state of synchronisation among neurons.
This synchronisation is therefore a hallmark of self-organising systems, where the state of each constituent depends, perhaps indirectly, upon every other component.
Neuronal ensemble displays fundamental behaviours, which can be summarised as the ability to maintain a state of self-organised synchronisation in face of external perturbation.

The graphs show Gaussian probability distributions that represent prior beliefs, posterior beliefs, and the likelihood of some data or sensory evidence as functions of some hidden (unknown) parameter.
The dotted line corresponds to the posterior expectation, while the width of the distributions corresponds to their dispersion or variance. Precision is the inverse of this dispersion and can have a profound effect on posterior beliefs. Put simply, the posterior belief is biased toward the prior or sensory evidence in proportion to their relative precision. This means that the posterior expectation can be biased toward sensory evidence by either increasing sensory precision – or failing to attenuate it – or by decreasing prior precision.

In Bayesian terms, the percept can be described as a posterior distribution, which is a combination of sensory information (likelihood) and prior expectations (prior). Two contrasting hypotheses have been proposed:
– enhanced sensory precision, that is, smaller σsens (left) vs.
– attenuated priors, that is, larger σexp (right).

Both hypotheses predict a reduced influence (bias) of the prior on the location of the posterior distribution (posterior mean).
However, these alternatives differ in their predictions for perceptual variability, which is determined by the posterior width: the enhanced sensory precision hypothesis should lead to reduced variability while the attenuated prior hypothesis should lead to increased variability.

Insight into our neurology evolved to assist us towards good understanding of how we can improve information uptake and decisioning. We can evolve, by training our capabilities to:

  1. Focused meditation enhances present-moment awareness of one source of sensory input such as the breath. It exercises the attentional brain network.
    Focused attention can damp down the brain noise of predictive processing
  2. Open awareness meditation withdraws selective attention in favor of non-judgmental, non-reactive, observational space in which thoughts and sensations appear and pass away.
    This progressively disables clinging to expectations generated by predictive processing.
    Instead of being immersed in thoughts or emotions a more open inclusive seeing presence emerges that detaches from and observes them.
    Within this open awareness, the transient appearance of an emotion like anger can be seen, as if from a third person perspective, as a process of angrying, different from being hijacked by the emotion and immersed in experiencing yourself as an angry person.
    The open awareness of seeing the angrying versus being an angry person offers the option of choosing between those alternatives. Ditto with being able to distinguish being a fearful or desiring person from observing yourself fearing or desiring.
    Open monitoring expands awareness to permit seeing without being the noise.
  3. Further deconstruction of predictive processing occurs in the non-dual meditative process in which the observer present in focused attention and open monitoring meditation.
    Subject and object disappear. Awareness means being aware that we are present without being something as such.
    Further expanded awareness can remove the dualistic observer altogether, entering the space from which everything rises.

Each meditation technique uniquely deconstructs the mind’s tendency to project the past onto the present, and reveals the plasticity of the human mind.

Sensemaking, based on the Cynefin framework is also based on the need of the capability to “unlearn”. Instead of focusing on a future ‘to-be’ and teleological ideation, the sensemaking starts with a sound understanding of the present and the possibilities to evolve.

This really means, how do you constantly look around you all the time for new ways, new resources to learn new things?
That’s the sense of entrepreneur
I’m talking about that now, in the networked age, gives us unlimited possibility.


Key in the understanding of the present is to have the capability and tools to “listen” in order to learn from the mapping and understanding of entangled complex situations and decide afterwards upon the first best move.
The Complex Adaptive System (or Complex domain) is the most important domain reality is present and presented.
The context determines what you can do. There are no context-free tools. Tools (and architects & architectures) need to become context-aware and context-dependent. So you need multi-methods & multi-tools to solve the complex space.
From the context and complex domain, building evolutions and solutions is done by conducting experiments that are safe to fail.
Cynefin calls this process “probe–sense–respond”, or in somewhat more words: : give-it-a-try (it might help), look what comes out of it (observe the results), and correct (or re-do).
Complex systems have the attribute “the only way to understand the system is to interact”. It sounds much like every-day life, especially if you see how babies and youngsters learn 🙂

All three have basic behaviour and interactions in common.
I would like to try to summarise these as

  1. Start with interactions, free of models predicting what ‘should be done’.
    Leave the predictive model at home in the beginning.
  2. Observe the facts coming to you, without judgment and analysis.
    Just record and accumulate what happens and about the resulting effects
  3. Reinforce by your actions what you value (i.e. consider beneficial or like), in order to reduce your future ‘surprises’.
    Do not interact to predict future context.

This is all great. I like this need for observing before building context because somehow I’m a combination of aspects from scientists and artist. In doing so, I know and experience the mere fact that observation without judgment or expectation enhances the depth of the experience and increases the chances for better and deeper understanding.
Simply said: you can better ‘grow’ experiences and environments, instead of ‘constructing’ them.

As such, it all allows for the positive evaluation and acceptance of uncertainty and ambiguity.

The quest for precision is analogous to the quest for certainty and both – precision and certainty are impossible to attain

Popper (1974)

The ideas presented, also scale up to a higher level of teams and societies, and helping decision-making uncertainties for communities.
Foundation of this acceptance of governing VUCA is the key observation that we – as a nature and biology inspired person – like to keep things simple.

I need to rephrase this statement.
We “like” simplicity, but often fail to realize it.
In our constructed world, we keep on engineering on top of a complicated set of interdependent cause-relations decision-network. These decision networks build on top of our preferred assumptions and propositions. Since we do have these preference and prejudices, we should learn to engineer without “our darlings”, and open our thinking and design to the health (i.e. sustainability) of the solution, comparable to these of natural ecosystems with the concepts of resilienceefficiency, and robustness. Some advanced engineering concepts attempt to build these consideration, but the path to the engineering and realisation of real complex systems is still long.

Euclid taught me that without assumptions there is no proof. Therefore, in any argument, examine the assumptions. Then, in the alleged proof, be alert for inexplicit assumptions. Euclid’s notorious oversights drove this lesson home.

Eric Temple Bell (1949)

4 responses to “It all comes together in a perfect storm :: “Keep it Simple””

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