Understanding Zargham — structuring complexity

As explained in my first post, complex systems are not just complicated. Complex systems behave in ways that are hard to predict, they respond to local rules as well as overall dynamics.

To begin to order your understanding of complexity, this model can help. It considers the various aspects of complex systems, while at the same time giving you a visual structure.

Traditional silo’s, with layers/levels intersecting them

Pillars that represent life and the world at large

These four pillars represent the traditional ways in which we used to approach complex problem solving issues:
- Social
- Economic
- Technological
- Physical

These are the various ‘aspects’ of our lives. We are inherently social beings, that relate to each other and our environment. “What does it do for me?” Is a relevant, but admittedly self-centered question. We have economic relationships as wel, and our understanding of what economy is, shapes our interactions. Then there are the technological possibilities that support, shape and augment our relationships and transactions. Finally, there are the physical possibilities and limitations of our own bodies and those that our environment offers.

These fields used to be viewed as separate silo’s, but that does not really help to truly address complex network systems. In order to create a more holistic view, we can see how various layers intersect and interconnect all these fields.

Layers that represent the systems we can build

(These might also represent the systems that we are part of, but not yet fully understand)

Value flows

This layer shows us the macro state evolution, which is not just limited to displaying the end results of the underlying layers. It is also the layer where we try to set and measure our global goals for our complex system (which can actually span ~~the world globe~~ multiple planets).

Local agent behavior

What kind of local behavior results in the macro trends we want?This layer contains the mechanisms at work, the incentives offered and the local context. From this, the behavior emerges.

Interaction patterns

What are you allowed to do? This layer gives you the definitions of mechanisms and incentives, as well as the local constraints. It is theoretical/formulaic. Patterns can be designed, but also observed first and then formalized.

Trusted computation

We need to be able to trust the execution of the code. Blockchain technology is a way to cryptographically guarantee the execution of code. This is similar to how in the real world, some things are possible and others not because of the laws of physics. Resulting behavior is predicated on what is actually possible.

Durable data

Nothing is trustworthy if the data used cannot be relied on. This layer provides trustworthy state information. Again, similar to the real world: The state of the world is well defined. Matter and energy are in some state at any given moment in time.

From macro down to local, and back up again

Having traveled all the way down from macro to state, we can now move back up and see where we end up. 
- What does it mean to be in a particular state? 
- what it means to change the state?
- What are we going to build and explicitly allow?
- What will people do with that allowance?
- What macro results emerge?

Let’s expand on these interactions and intersections in upcoming posts. Let me know what your questions are!