The 10 Features of Complex Systems — Part 1

@created:: 2024-01-24
@tags:: #lit✍/🎧podcast/highlights
@links::
@ref:: The 10 Features of Complex Systems — Part 1
@author:: Simplifying Complexity

2023-06-19 Simplifying Complexity - The 10 Features of Complex Systems — Part 1

Book cover of "The 10 Features of Complex Systems —  Part 1"

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(highlight:: The Four Conditions of Complex Systems: Numerosity, Disorder/Diversity, Feedback, & Non-Equilibrium
Summary:
Now, in part one, we're going to look at the four conditions that we see in complex systems. They are numerosity, disorder and diversity, feedback and non-equilibrium. And then at the end of the episode, we're going to pull the four of those together and look at a central concept in complex systems, a concept of emergence.
Transcript:
Speaker 2
We're going to look at the four conditions that we see in complex systems. They are numerosity, disorder and diversity, feedback and non-equilibrium. And then at the end of the episode, we're going to pull the four of those together and look at a central concept)
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(highlight:: What is Numerosity in Complex Systems?
Key takeaways:
• Numerosity refers to many things interacting in many ways and many times.
• Different systems have different thresholds for numerosity.
• The number of ways in which even a small number of elements can interact can lead to interesting behavior.
Transcript:
Speaker 2
So let's start with numerosity. So in your book, or James Ladyman, you say numerosity of interactions or parts can produce dramatic differences in behavior. So what is numerosity?
Speaker 1
Numerosity is maybe a bit of a strange word. It just means many, many things are interacting in many ways and many times. Now how many is many is a question that is being answered by different systems in a different way, I guess? There is a fun example, which is an ant colony. How many ants does it take for a colony to function in the way we see it functioning in the forest? And depending on the colony type, you can put 100 of them on a plane and they will not do anything. They will just go around in circles and die. But if you put down 10,000, then suddenly things start to happen. And other systems have different thresholds, if you like, of how many is many. You know, the smallest brain we know about is I think 300 something neurons. And then it goes up to millions and trillions and so on in more developed brains. So how many is many is different for different systems? What's important though is not just how many things there are or how many elements, but even if you have just 300 elements, the number of ways in which they can interact is exploding exponentially. And that's what is really so crucial for something interesting to happen is the interactions between the many parts.)
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(highlight:: The Abstraction of Information in Complex Systems
Summary:
In complex systems, interactions between agents involve an exchange of energy, matter, or information.
Information, as an abstract concept, plays a crucial role in studying complex systems. It can be represented through words, numbers, or other means.
Information allows us to communicate location, as well as convey news or advice in various domains such as economics or biology.
In biological systems, information flows into the system through pathogens or viruses, and this information is then abstracted within the system to activate specific cells or particles.
Transcript:
Speaker 2
These interactions between these agents is essentially an exchange of energy, matter or information. It's really worthwhile pulling the three of them apart. Bearing in mind that I think for many people common to complexity, this concept of information is always a difficult one.
Speaker 1
It is because it's abstract. We all have a sense of information. You know, I read the news every day and I get some information. It's an abstract representation of something. So information can be the information about location. So I'm communicating a location, not by being at that location myself, but by some are representing that in words or in numbers or in something else. So information is an abstraction. And that's the beauty of it. That's why it's so important in complex systems because so much happens in studying them is by abstracting things away from the physics. So information can flow into a system that could be for humans that could really be news. You know, the economy works a lot on the basis of information. You hear about certain stocks that you should sell or buy or whatnot. The same though is true for biological systems. So the immune system, you can think about it as information coming in. Of course, pathogens come in, virus comes in. But then the fact that that is entering the system is being almost abstracted within the system so that T cells are being activated based on that information, which is a biological representation, Of course, in terms of cells and other particles.)
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- [note::"Information is an abstraction"]

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(highlight:: The Importance of Energy in Complex Systems
Key takeaways:
• Complex systems are sustained by the influx of energy.
• The entire earth is sustained by the energy influx of the sun.
• There is energy out flux because energy is being radiated back into space.
Transcript:
Speaker 2
How does exchange of energy work?
Speaker 1
Yes, so a simple example in a physical system, it's the influx of energy. I mean, the entire earth, the entire Gaia, some people call it the Gaia of the earth, is there because of the energy influx of the sun. And if the sun is gone, then the system can't sustain itself. And at the same time, there's also energy out flux because energy is being radiated back into space. So many, if not all complex systems are sustained by the influx of energy, chemical reactions.)
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(highlight:: The Necessity of Disorder & Randomness in Complex Systems
Key takeaways:
• Disorder and diversity are important behaviors of a system which is somewhat random and beneficial for the system to adapt and react to unknown things.
• Randomness is necessary for systems to explore and discover new information, as in the case of end colonies or the immune system.
• Disorder and randomness are necessary conditions, not something we wish wasn't there, for structure to arise in complex systems.
Transcript:
Speaker 2
So number two is disorder and diversity. Tell us about those.
Speaker 1
Disorder and diversity are the behavior of a system which is somewhat random. So it means if we take the immune system where the T cells are wandering around the body and they don't have a determined path that they follow along. And then at that path, maybe they hit the pathogen and they will be activated. But instead they clearly walk around randomly, they swim around randomly. And it's this randomness that's important because that way they will visit at some point every location. At some point every location is important to make sure that interactions can happen, interactions with other parts of that immune system. And that way signals can be propagated. Whereas if everything was deterministic, then the immune system would be able to react to unknown things, which is what it's there for it to do. Maybe it's somewhat easier example is this end colony, which I keep returning to because it's so visual in its randomness. And and is being sent out. Has the task of forging and it's it will just stop walking in some random direction until it hits on something either food or a signal from another end, which is back to information, which Will guide it towards a food source. And new food sources can only be discovered if there's randomness in the system, because the information about food source is not there to begin with. It can only be created through a random exploration of the space.
Speaker 2
This is I think one of the really interesting concepts that if you have a very Newtonian worldview that's like how to get your head round. And that is that what we're seeing with complex systems is that this disorder, this randomness, as you've said in our previous episode is is a feature of the system. It's something that's beneficial. It's something that gives it the power to adapt what he does. And if in the absence of that disorder, you essentially just get locked into how things work. Correct.
Speaker 1
And that's why we put disorder here as a necessary condition, not a something that we wish it wasn't there. We wish it was there. Disorder is really important for anything. I say interesting for now to arise, but certainly for structure to arise, it will be necessary.
Speaker 2
And that's fascinating. You're saying like for a structure to arise in the complex system, the disorder is actually necessary. Yes.
Speaker 1
And I guess we will come back to other positive side effects of disorder. But this one is it is the motor, if you like, of structure to arise. And on its own, it wouldn't be enough.)
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Increasing Returns (Order in a System is a Product of Disorder, Numerosity, and Feedback
Summary:
Disorder, in tandem with feedback, leads to order.
Feedback occurs when information is transmitted and found by others, creating a cycle. This feedback, combined with disorder, results in the phenomenon of increasing returns, where random decisions influence subsequent decisions.
Increasing returns in a system depend on disorder, feedback, and the involvement of a sufficient number of individuals.
Transcript:
Speaker 1
The next one on the list will be feedback. So the disorder only in tandem with feedback is going to lead to order. And the and trail again, an example, the feedback is coming from one end going out, finding something interesting as happenstance by accident. And then it leaves information. Another and finds it. And that's where the feedback starts. And this feedback is, you know, just like, I believe, Brian Arthur was talking about increasing returns. Initially, something random happens. Someone makes a random decision and a few more, say, people make a random decision. And that leads other people to not make a random decision, but make a decision based on that previous one. So this increasing returns phenomenon is a combination of disorder and feedback. And of course, the morosity, you need a few people to make it happen.)
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(highlight:: The Diversity of a System is Another Kind of Disorder
Key takeaways:
• Diversity is an additional kind of disorder that can be crucial for system function.
• Simple complex system models have identical elements, whereas the immune system has different types of cells and workers.
• Diversity in complex systems such as the immune system refers to non-identical elements.
Transcript:
Speaker 2
What's the difference between disorder and diversity?
Speaker 1
You know, we know diversity from say a group of people is diverse because you have different ethnicities or different ages or whatnot. And the most simple models of complex systems just took identical elements and put them together. And it turns out that when you look closely at very intricate complex systems like the immune system, you don't have just one type of cell or an ancole and you don't have just one type of Worker, you have different types of workers. So diversity is, if you like, an additional kind of disorder that not every element is exactly identical to every other element, which can be very crucial for the system as a whole to Function.)
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(highlight:: What is Feedback in Complex Systems?
Key takeaways:
• Feedback is reacting to something that happened before.
• Feedback is the dependence on previous states in a complex system.
• Simple systems do not exhibit feedback.
Transcript:
Speaker 2
What is feedback?
Speaker 1
Feedback is reacting to something that happened before. So it can either be something that an element has done before, a location element has been before. It can also be feedback through another element's actions or another element's locations. And in that sense, feedback is the dependence on previous states. So if you turn this around and take a system which is not complex, it turns out to be not easy to find. But a box filled with a gas, we consider it to be not complex. The molecules will move around in that box. It's a box filled with air if you like. But it doesn't matter whether you look at this box a year ago or a minute ago, it all looks the same. And there won't be any dependence on the current state of previous states. And that is different for a complex system. There is a dependence on where the system is now and it depends on previous states.)
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(highlight:: What is Negative Feedback in Complex Systems?
Key takeaways:
• Negative feedback is a form of stabilization mechanism for a system.
• Without negative feedback, systems such as populations would continue growing indefinitely.
• Negative feedback leads to slowing down of growth and diminishing returns.
Transcript:
Speaker 2
What does negative feedback do?
Speaker 1
Negative feedback, it sounds like a nuisance, but it's actually a form of stabilization mechanism for the system. It means that a dynamic is being toned down if you like. So without negative feedback, for example, populations that are growing in size would keep growing, that's what populations like to do. But because they're dependent on the provision of some kind of food source, there will be eventually slowing down of that increase. And of course, diminishing returns, which we've heard about in economics, is such a negative feedback.)
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(highlight:: What is Equilibrium?
Transcript:
Speaker 1
Equilibrium is a state where something doesn't change anymore. It stays where it is. And that can be a very static state where really nothing changes, things just stand still. And that by itself excludes it from being a complex system because a complex system is constantly changing. Which is different, by the way, from what is maybe created by a complex system. So that difference is quite important. The difference between, for example, the honeycomb, which is created by a honeybee hive, the honeycomb is a static system and it's beautifully ordered, but it's the product of a complex System. So the complex system, which would be the honeybee hive in this case, is never still, is never static. Equilibrium, though, can also exist as in a dynamic form. So you can have the same amount of things flowing in and flowing out. Say a lake can be an equilibrium. There's the same amount of water coming in as it's going out. And this lake is maybe a better example of what non-equilibrium means. Because inside of that lake, lots of things are thriving on this water coming in and going out. There are obviously the fish that are there, but also algae, bacteria that are changing because they get constant feed in of water and of nutrients that are coming with the water. So the system itself, which is this lake ecosystem, is not an equilibrium because it's constantly changing, forming. Maybe one species is coming in and finding a niche within that ecosystem. And even the geological formations of the lake are never completely static. They're constantly changing. So it's what happens within this, if you think of the complex system as being defined, where water is flowing in and water is flowing out. What is happening in between is what makes the system complex.)
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(highlight:: Understanding Emergence in Complex Systems
Transcript:
Speaker 2
You've said there's no conception of complexity or complex systems that does not involve emergence. So what is emergence?
Speaker 1
Emergence is a concept that really needs to be picked apart because it's so full of expectations that emergence is a thing, but emergence is not a single thing. Again, it's the process of something coming about through other processes. And we've spoken about these fundamental processes of fundamental features of complex systems. What happens because of these features is what emerges from these features. So emergence, I say it in a nutshell, almost quoting Philip Anderson, who said it very distinctly, which is emergence is in all complex systems, the whole displays behavior that the Individual parts cannot. So again, emergence is the whole that is displayed in terms of behavior that the individual parts cannot display on their own. And that can be a lot of different things, but it certainly, it is what makes us wondrous, what makes us want to study these systems. And it makes it not obvious you can't get an ant trail with a single ant, you can't get a colony with a single ant, you can't get increasing returns with a single agent. In a way, it doesn't even make sense to speak about these things for individuals. They only make sense once you put a lot of them together.)
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