So, if networks are the future, how do we set them up? We are so used to using engineering that we can default into using engineering rules.
Real networks ALL "Emerge".
This sounds weird but we actually have a lot of experience in how to do this. It's called Gardening! It's also called Parenting. When we apply machine principles to gardening we get monoculture agriculture. When we apply machine principles to parenting, we get badly adjusted children.
When we apply the Rule #4 we get life and the full potential of the network, the garden and our kids.
In this part of my book, You Don't Need a Job, we look at how the rules of Emergence work. They apply of course not only to your work network but also to how you parent. I will show you both.
For more on this - My book is here on Amazon
If this all looks a little abstract, tomorrow I will share with you how we used these ideas to transform a public TV station.
Rule#4 Emergence is How Real Networks Grow
source: Perennial Garden Plants
This is a perennial garden. Once the gardener has set the conditions up correctly, the garden does all the work.
This process is called emergence. It is as different from engineering as dynamite is from the atom bomb. Engineering uses mechanics, emergence uses physics. It is in this process that the quantum improvement in performance between an engineering culture and a network culture will be seen.
The challenge for us today is to find out how to set the conditions for emergence to occur. The answer is to be found in the concept of initial conditions.
All natural things, living or not, develop when they find the ideal starting conditions. Hurricanes don’t happen in January. They happen between June and November when the initial conditions of temperature and water are right. Without these conditions, a hurricane will not develop to its full potential, but with the right conditions it will. It will do this all by itself.
Human social networks are the same they emerge when the optimal conditions for development take place.
We can start to explore this idea best by looking at how our children develop, or do not, to their full potential. If we can understand this, then we can understand how to set up the ideal initial conditions for a human social network. For we know that in nature all development is fractal. What happens at one scale happens at all scales.
Source - Link Santa Fe Institute
This figure shows us what it looks like when a child acquires language. What we see is a pattern that becomes denser and denser as more and more connections are added. Then, at some point, the new system takes off and has a life all of its own. This is emergence. Emergence is how life itself begins. At some point of connection inside an ideal environment, life itself emerges. This insight makes me wonder what will happen after 100 years of humans being connected as we are today? Is this how language itself emerged after millions of years of people sitting around a campfire?
We know now what the optimal initial conditions are for human language and development so we can apply this knowledge to human networks. (A full explanation of this process is here if you wish to explore this.)
To initiate the process of human development, children need to be touched a lot. They need to hear a lot of words. Infants also need to hear these words in the right social and cultural context. The right context is in a firm, safe and loving family culture.
As you will see, initial conditions are also time sensitive. The window for development is largely closed for a child by 3.
This is what success or failure looks like.
We can see two separate trajectories that diverge over time to produce a significant difference. At 2 years of age one child can understand 300 words and the other 150. Not much of a difference. However, look at the trajectory. In the case of the 300 word child, by 15, she will be at 2nd year university level. The 150 word child will be stuck at grade 5.
The difference looks tiny, but that is the key to understanding initial conditions. Tiny differences at the outset extend over time to huge differences. Trajectories have a power of their own.
Willms’ and Hart and Risley’s work shows us that family culture is how initial conditions are set for every human being’s development. The optimal culture sets the maximum amount of trust.
Willms’ team identify the three key family cultural groups as being:
Authoritative – Parents who establish a warm and nurturing relationship with their children, but set firm limits for their behaviour.
Authoritarian – Parents who are highly controlling, requiring their children to meet an absolute set of standards.
Permissive – Parents who are overly nurturing and who provide few standards for behaviour and are extremely tolerant of misbehaviour.
The Willms research informs us that the poorest learning and development outcomes are found in families that have authoritarian and permissive cultures. Most machine organizations have these kinds of cultures too.
I think it follows that human culture is the driver for human social networks, for trust is the critical element.
In summary, human development is tied to initial conditions that promote trust and then exposes the child to the maximum amount of the right patterns. If these conditions are applied in a time sensitive manner, then emergence will take place. If done very well, the trajectory will take the person to her full potential.
What works for you and me as individuals, will work for groups.
For this is how natural systems work. They are fractal, they are the same at all scales. The brain and the universe share the same organizational pattern.
However, that is not all we need to know. If we were planting a perennial garden we would also need to know what kind of mix of plants is best. For we know that, even with the best growing conditions, a garden that reaches its potential must have the kind of reinforcing diversity that will drive good health and resilience.
There must be a healthy iteration between the elements in the mix.
In a later post we will talk about the "protocols" that all networks have in order to connect and have great complexity and so life. The good news is that no real network has more than 4 of these. The complexity comes from their iteration. So they are in fact easier to set up than a traditional organization that depends on thousands of rules.
All is in my book - You Don't Need a Job
