I was taking a course called "System Dynamics and Control" when I was a mechanical engineering student. At that time I realized that this is how human brain deals with complexity. There is no way to know everything. Instead we experience things and take feedback from them then we adapt ourselves to the conditions. For example we assume that we are intelligent enough to pass an exam without studying it. When we fail the exam we realize that this is the wrong way to approach and we change the strategy. Understanding complex systems help us to understand ourselves. Thanks for the videos.
I like the idea of complex systems because it gives a scientific explanation for a lot of ideas in philosophy and eastern religions. Like for example the idea of letting go of the desire to control and plan everything around you because this approach often ends up giving you exactly the opposite of what you want. We cannot hope of being in control of a complex system. The best we can do is learn to live in harmony with it.
Have you heard about Agent-based modelling? Coz it ABM covers the limitations of systems dynamics model i.e systems dynamics is aggregrated and homogenoues with no Time-Location constraints,missing the details. ABM covers the big picture as well as the details.
My only real problem with systems dynamics theory (at least as presented here, and commonly elsewhere) is in some of its basic assertions, such as how systems tend toward equilibrium. This is just plain wrong outside of a very specific and very rare type of dynamic systeme: A closed, iterative system. That kind of system is hard to find in reality. Truth is, system interfaces (the interfaces between distinct systems) disequilibriate, and most systems change continuously (usually within a metastable framework). Entrainment through shared, predictable behaviours and standard processes gets around this by, in essence, embedding the interfaced systems within a shared system. This is part of why this error persists in the theory, because hidden (or ignored) entrainment makes embedded systems appear discrete.
The Euro, for one. Have a look at inflation rates across the countries that eventually joined the Euro prior to and after the introduction of the currency in the late 90s. Note that the convergence started earlier with the Maastricht Treaty. A more straight-up, simple example is the synchronisation of metronomes via entrainment. Place x metronomes on a board, get them going. Then place the board on two coke cans so that it 'swings' according to the ticking of the metronomes. The devices will self-synchronise (there are videos of this on CZcams). It's an important concept in economic regime change, see e.g. "Black Swans, Lame Ducks" (Blyth and Matthijs, (2017)) in the Review of International Political Economy. In fact, you could easily argue that the entire global financial economic sector is a highly entrained, highly complex, tightly coupled system. They are all working toward the same purpose - maximal value extraction to shareholders - and this has turned what was once a loosely coupled constellation of individual actors across multiple markets and geographies into a tightly coupled complex system whose entrained characteristic (said value extraction) has become maximised to such an extent that it has become destructive, and the systems interfacing with it but not entrained (and thus encapsulated) by it are now responding in a disequilibriating manner (hence, the current wave of populism across the world). This is... very quickly and shoddily summed up. But I hope it gets the point across? If the natural and expected tendency predicted by system dynamics theory is for all these systems to tend toward equilibrium, we wouldn't see these periodic upheavals.
The highlight of my days are when you upload videos of systems innovation.
I was taking a course called "System Dynamics and Control" when I was a mechanical engineering student. At that time I realized that this is how human brain deals with complexity. There is no way to know everything. Instead we experience things and take feedback from them then we adapt ourselves to the conditions. For example we assume that we are intelligent enough to pass an exam without studying it. When we fail the exam we realize that this is the wrong way to approach and we change the strategy. Understanding complex systems help us to understand ourselves. Thanks for the videos.
I like the idea of complex systems because it gives a scientific explanation for a lot of ideas in philosophy and eastern religions.
Like for example the idea of letting go of the desire to control and plan everything around you because this approach often ends up giving you exactly the opposite of what you want. We cannot hope of being in control of a complex system. The best we can do is learn to live in harmony with it.
Would you explain this idea with more profundity!
Have you heard about Agent-based modelling?
Coz it ABM covers the limitations of systems dynamics model i.e systems dynamics is aggregrated and homogenoues with no Time-Location constraints,missing the details. ABM covers the big picture as well as the details.
Loved it
My only real problem with systems dynamics theory (at least as presented here, and commonly elsewhere) is in some of its basic assertions, such as how systems tend toward equilibrium. This is just plain wrong outside of a very specific and very rare type of dynamic systeme: A closed, iterative system. That kind of system is hard to find in reality. Truth is, system interfaces (the interfaces between distinct systems) disequilibriate, and most systems change continuously (usually within a metastable framework). Entrainment through shared, predictable behaviours and standard processes gets around this by, in essence, embedding the interfaced systems within a shared system. This is part of why this error persists in the theory, because hidden (or ignored) entrainment makes embedded systems appear discrete.
SantaBJ Interesting, can you give an example of such entrainment?
The Euro, for one. Have a look at inflation rates across the countries that eventually joined the Euro prior to and after the introduction of the currency in the late 90s. Note that the convergence started earlier with the Maastricht Treaty.
A more straight-up, simple example is the synchronisation of metronomes via entrainment. Place x metronomes on a board, get them going. Then place the board on two coke cans so that it 'swings' according to the ticking of the metronomes. The devices will self-synchronise (there are videos of this on CZcams).
It's an important concept in economic regime change, see e.g. "Black Swans, Lame Ducks" (Blyth and Matthijs, (2017)) in the Review of International Political Economy.
In fact, you could easily argue that the entire global financial economic sector is a highly entrained, highly complex, tightly coupled system. They are all working toward the same purpose - maximal value extraction to shareholders - and this has turned what was once a loosely coupled constellation of individual actors across multiple markets and geographies into a tightly coupled complex system whose entrained characteristic (said value extraction) has become maximised to such an extent that it has become destructive, and the systems interfacing with it but not entrained (and thus encapsulated) by it are now responding in a disequilibriating manner (hence, the current wave of populism across the world).
This is... very quickly and shoddily summed up. But I hope it gets the point across? If the natural and expected tendency predicted by system dynamics theory is for all these systems to tend toward equilibrium, we wouldn't see these periodic upheavals.
Gold rushes always collapse...
There is currently a gold rush in Virginia USA ..... building data centres 😘