Networks operate differently from industrial age's factories, mass movements, parties and mass media because they're largely peer-to-peer instead of top down projects or bottom-up power-grabs.  

 

Why are these "rules" important?  Because they dominate how societies, economies and politics are organized on the planet today - they are the tools of monopolists and autocrats, but also the antidote to them.

​

   

1. Small worlds: digital content travel at lighting speed around the world without "asking for permission."

2. "Weak" Ties.  The content and links create informal coalitions of like-minded communities outside of formal family, work and political ties.  Weak links should be called informal alliances. 

3. Homophily.  Lightning speed content connects to people "like us" and disconnects "others." Basic survival network mechanisms like "availability" (premium on sensational and immediate news) and confirmation bias (looking for information that supports our beliefs) amplify and magnify homophily.

4. Power Laws.  The very geometry of complex networks creates or increases stratification and inequality by favoring upstart innovators, agile incumbents and connected gate-keepers 

5. Diffusion. Innovations, insurgencies, creativity, contagion (like a virus) don't work the way industrial institutions work: through top-down laws or bottom-up power grabs.  Innovations "diffuse" via contacts between peer groups, radiating outward from the most concentrated parts of a system to its periphery.  The inequality of power laws can only be overcome by community-to-community diffusion of power from concentrated hubs to their adjacent nodes, not by "reform" from above or "revolution" from below.  However, epidemics, terror cells and fanatics work the same way.

6. Feedback. The parts of any system interact.  That creates feedback, where the exchange of energy between seemingly "unimportant" parts of a system get amplified in ways that unpredictably change the character and behavior of a system as a whole.  Cohesive feedback that strengthens a system works against disruptive feedback (physics' names for these types, "negative" versus "positive" give the wrong impression).  Normally they cancel each other out.  But in a younger system cohesive feedback tends to bind the system together, while late in a system's lifespan, rigidity sets in and disruptive feedback begins to pull the system apart. 

7. Hebbian Synchronization. The central insight of Donald Hebb about cohesive feedback: the parts of a network that work together all the time create strong ties.  "Cells that fire together bind together." Fighting together for a common cause creates common bonds.

8. Allometry.  Different parts of any network growth differently because some parts form quick connections (like the brain or big cosmopolitan cities) while others take more time (like limbs, backbones, rural centers) - especially the ones that have to carry the weight of a growing system.  As a result, in any system, organism or network changes its character (who it looks and operates) based on how its parts grow.  Growth never happens at the same rate in a country or a body or ecosystem.  

9. Scale Variance.  Beyond the different rates of growth in a system based on how burdened its parts are with the physical world, there are different rules that govern different scales.  The tiny world of quantum particles is relatively free of "normal" world constraints in everyday life, so it's rules are more fluid.  The great cosmos reveals a whole set of rules - like relativity's equivalence between matter and energy - that everyday people generally don't experience in the "normal" world of Newton's physics.  In the same way, the family and local level of society's operate differently from the politics of a nation and the even more complex interactions between nations and of the global environment.  Physics's study of pattern of self-similarity shows that these different levels share patterns - they look like each other in various ways - but don't be fooled.  It's a big mistake to impose "higher order" rules - universal ideologies - on "first order" communities without taking into account local conditions.

10. Entropy.  Any system of beliefs like brands, social orders, ideologies eventually run out of steam. Physicist Geoffrey West pioneered adapting complex physics to societies. As he puts in in Scale: "Because energy underlies the transformation and operation of literally everything, no system operates without consequences. …As we begin to lose the multiple localized battles against entropy we age, ultimately losing the war and succumbing to death. Entropy kills.”

11. Percolation.  Once a system - from a pot of boiling water to a market or society - gets past a tipping point in how it absorbs energy it can't go back to its initial state unless its heat goes down or it transforms into something new.  Societies transform or die when they no longer channel the energy of their people.Transformation, like percolation, means changing the outer form while retaining the essential substance, the binding myth, of a nation.

12. Multiscale Connectivity.  Network scientist Duncan Watts adapted the term to mean organizations that interconnect different levels of society or organizations and work across levels and disciplines.  It is the opposite of industrial command-and-control systems, or libertarian laissez faire.  It is why "campus" design has replaced "factory" models and is critical to re-inventing government and policy.

13. Complexity: incessant feedback between the parts of a network means the system can't be understood from its constituent communities and their interactions. You have to harness waves through adaptation instead of dictating outcomes.  A better word, less scary, is diversity.

14. Chaos. Feedback also makes the movements of markets, technological waves, content, contagions, ideas and insurgencies impossible to predict with precision. Instead, science, art and entrepreneurs track-and-trace their work and threats real-time. Creative endeavors as well as insurgencies and contagion follow a so-called logistic growth curve: bustling but undercover nascency, explosive ascendency, grinding consolidation and burn-out.  Chaos is misleading: movements have patterns.  But chaos in the physical sense is the opposite of chaos as the word originated, implying disorder.  Chaos among particles in a system is the opposite, it's the hidden pattern and order inside a seemingly disorganized chaotic system.  So it's better to call the study of chaos the understanding dynamism. [see the chart at the header of this blog]

15. Regression to the mean. In the end, any system, society or market in turmoil will find a way of reverting to its longer-term trend.  Democracy is a system, adopting it takes centuries.  Once ingrained it tends to endure despite giant leaps toward autocracy.