(highlight:: The Six Major Products of Complex Systems
Transcript:
Speaker 2
This one is all about the products that come out of complex systems. And they are spontaneous order and self-organization, non-linearity, robustness, nested structure and modularity, history and memory, and adaptive behavior.)
- Time 0:01:47
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(highlight:: Understanding Spontaneous Order and Self-Organization in Complex Systems
Key takeaways:
• Self-organization is a process that occurs without external control.
• Living systems, such as beehives, exhibit self-organization through division of labor and nest building.
• Chemical reactions demonstrate self-organization through the emergence of structure from a disorganized state.
• Self-organized behavior in immune systems is distributed and not centrally controlled.
Transcript:
Speaker 2
So, let's just jump straight into spontaneous order and self-organization.
Speaker 1
That is probably what captures our interest most of all these features that you've mentioned, Sean. This is what makes them interesting because it's something that's very visual, right? Self-organization. We've spoken about the lack of a central control. So, that's in the word self. The system does it itself without something externally or some central element doing it for it. That's the self. And the organization is that something comes out of nothing. The nothing in this case is what we've spoken about before, so it's the disorders, the feedbacks. So, out of these things, something arises and that is order structure. We had several examples already spoken about in the show and I've mentioned chemical reactions because it's so visual, you have, initially, some liquid which doesn't have any structure To it and then you let it go for a while. And suddenly you see circular forms, you know, circles, colored circles coming out. That is a form of self-organization. Then there are, of course, all the living systems we've spoken about that would be the beehive has a form of self-organization. Initially, a colony starts out small and then you have the division of labor which at some point is organizing itself. You have the nest site that's being built is the form of self-organization.
Speaker 2
And the key bit there is that the individual bees or ants in and of themselves don't really do much. It's only when you put them all together and make them interact that we get this.
Speaker 1
Yes, it's a process, right? So the system starts out in some state which is, if it really starts out, it's a very disorganized state. So in the case of the chemical reactions, initially you have no structure whatsoever, you've just poured the chemicals in. It's at the very beginning. For a beehive, at the very beginning you would have a queen and a small set of workers. There is no nests, there is no division in which bees care for the queen and which bees carry in the food and the water and so on. You could even say in an immune system, the response to a virus initially, the system is in some state which is already ordered, of course, but once the pathogen comes in, then the system Self-organizes the response. And that is not centrally controlled. It is happening in a very distributed, like we've heard explained, a very distributed way. This response is a form of self-organized behavior.)
- Time 0:02:04
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(highlight:: Non-Linearity in Complex Systems: The Response is not a Linear Function of the Input
Transcript:
Speaker 1
Nonlinearity happens in so many ways and some are more simple, more trivial than others. One form of nonlinearity is this exponential growth that we've heard about. For example, in growth of a virus when it enters a host, then it replicates. And this replication is not that after a day there will be double the amount and after a second day, then there will be just a little bit more than double. That's not how it happens. It will be doubling every day, let's say, or every few hours depending on the virus, which means that the number of viruses that you find is not just the same as the number of days you've Waited, but it is way, way more than that. And this exponential growth happens in, but scaling laws are another example of that form of nonlinear growth. So, especially in terms of time, these systems have a nonlinear change over time.
Speaker 2
Tipping points, they are form of nonlinearity.
Speaker 1
Tipping points are absolutely form of nonlinearity. So, for one, tipping points, the different aspects of tipping points that show this nonlinearity, the most obvious one is, of course, that a tipping point is something where a system Is in the somewhat unstable state, and it keeps being nudged from the outside, which we've heard about before. And a small nudge, if it is away from a tipping point, a small nudge will just cause a small reaction of the system, slight adaptation, slight adjustment, whatever. But when it is close to a tipping point, a small nudge will cause a huge change in the system. So, that is a form of nonlinearity in the sense that the response is not a linear function of the input, and that's particularly strong in tipping points, that's different.)
- Time 0:04:51
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(highlight:: Robustness in Complex Systems: How resilient the system is to outside disturbances
Key takeaways:
• Robustness is an emergent feature due to conditions like disorder and feedback which make the system robust in the face of small perturbations and damage.
• The interplay between positive feedback and disorder is responsible for the emergence of robustness.
• Decentralized control contributes to the system's ability to survive even when parts are removed.
Transcript:
Speaker 1
Robustness is somehow there in all of these emergent features, but in and of itself, it is emergent, again, because of the conditions, the disorder, the feedback, they are actually Responsible for something to be robust. And the system as a whole is robust in the sense that, you know, small perturbations from the outside and nudge, slight damage to the system. It does not stop the system from functioning or the system from self organizing. It is, in that sense, an emergent feature, so it's a product of the conditions.
Speaker 2
And part of it from, and we obviously talked about it's part of it's from the sort of the interplay between positive feedback trying to put loads of order into the system, and you have Your noise or disorder trying to take away that nice order and it's the tug of war between the two of them. The other point you make that I really enjoy is that you can grab a handful of hands out of the end colony and you don't kill the colony. And that presumably comes back to this concept that it's not centrally controlled. It's all dispersed throughout the system. So taking away a little chunk doesn't disable it. The same as we're carving off a piece of the internet doesn't kill the internet.)
- Time 0:07:07
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(highlight:: The Difference Between Nested Structure and Modularity in Complex Systems
Key takeaways:
• Nested structure involves zooming in to see multiple levels of structure, while modularity involves separating a system into parts with different functions.
• Democracy is an example of nested structure where decisions are made on multiple levels, from parliament down to local councils.
• Modularity is exemplified in the brain, where different parts are responsible for different functions.
• Structurally, networks can also exhibit modularity.
• Nested structure involves hierarchy, while modularity does not.
Transcript:
Speaker 1
Nested structure means that you zoom in and you see no structure and you zoom in again and you see no structure. And that is even true on a somewhat more abstract level, say a social group. Democracy is one of my favorite examples here, where you have certain decisions that are being made on a very high level, say the parliament. But then you zoom in and you ask, well, how do these parliamentarians get to their power? Well, that because they've been elected by a certain subgroup of people and then you look at that subgroup and you see you have local city councils and you look into the city councils, So on and so forth. So nested structure is that you see at some level a structure you zoom in, you see another one. Modularity is slightly different. It's more to do with function. So modularity means that the system is separated into parts, and these parts take on different functions. The main example is the brain, different parts of the brain, they all consist of neurons and little other bits and bobs, but essentially neurons, and there's parts of the brain that Are responsible for the vision parts of the brain that are responsible for the rotary functions and so on. So modularity is to do with function and it separates the system into subsystems that are somewhat on an equal level. You see that structurally networks networks have been spoken about here, where parts of the network are the brain is a network right and part of the network are responsible for different Things. So that's a form of modularity as well.
Speaker 2
So you see that nested structure is has hierarchy, whereas modularity doesn't. Is that the role solo on the same plane.)
- Time 0:10:27
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(highlight:: History and Memory in Complex Systems
Key takeaways:
• History and memory are two distinct concepts.
• History refers to the origin and development of a complex system.
• Memory is stored within the complex system and can be older than the elements of the system.
• The brain, immune system, and colonies can all have memory.
• Memory is stored in biological and physical form, and reactivated when necessary.
• Memory is a tool that the system uses to its advantage.
Transcript:
Speaker 2
So history and memory. It's history and memory.
Speaker 1
We like to distinguish between history and memory because history is you can think of the history of a complex system. How did it come about that is, you know, how did if you like any the history of any living complex system goes back to origin of life which goes back to the origin of the universe and so on. So the history is really in a way as far back as we know at the moment. And they all do have history, if nothing else because they come out from these conditions that we've spoken about disorder feedback and so on. The memory is within the complex system. Of course, the brain has memory. And that's what it's for. Remember things we store them in in neural structures in the brain. The immune system also has memory. It remembers pathogens it's seen before, even if it was years and years ago, and it stores that memory in a biological physical form. And it reactivates it whenever it's needed. And colonies can have memory. So the thing about memory, what makes it so interesting is that the memory of a system can be older than the elements of the system, which means. If it has seen a pathogen 10 years ago, there might not be a single T cell. That's the same anymore compared to 10 years ago, but the system has remembered that's memory and that's fascinating. And the same in fact can be true about and colonies they can remember sources of good food from, you know, this is being sort of passed on from generation to generation so even though the Food source was discovered many years ago. And none of the answers that old, but the ancolony as a whole has kept that memory. So memories stored within the system and it is something that the system uses to its benefits.)
- Time 0:16:29
- history, memory, complex_systems, 1todo evernote,

(highlight:: Memory is a Persistence of Structure and Non-Living Systems Can Exhibit It
Transcript:
Speaker 1
We like to state things as general as possible. So memory is something, you know, the way I've spoken about it until now, it's something just more intuitive, I guess. I remember a face or a song or whatever. But memory is in a way a persistence of structure. And the song, if I remember a song, it's a persistence of structure in my brain. But persistence of structure, I can also find a non-living systems. So if you have, for example, Jurassic Coast and South of England comes to mind for some reason, I don't know. It's a beautiful structure. And it has come about through this interaction between, of course, the ocean and the coastline. And it's been there for a long time. It's, you know, slowly changing over time. If you like, it's a way of, it is the memory of these past interactions between the ocean and the coast. And there's no living system involved, not in the way I'm speaking about it. Now it is really just interaction between physical elements. And it is a form of memory because it's persistent structure.)
- Time 0:20:20
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(highlight:: Adaptive Behavior in Complex Systems
Key takeaways:
• Adaptive behavior is something associated with complex systems that are alive or functional.
• Complex adaptive behavior means the behavior is there and it's adaptive, changing according to changes in circumstances or memory.
• Adaptive behavior is a form of robustness and resilience, making a system less vulnerable to perturbations.
Transcript:
Speaker 2
Adaptive behavior.
Speaker 1
What's that adaptive behavior is certainly something which we would only associate with complex systems that are alive or functional. You often see people talk about complex adaptive behavior, which I think is saying the same thing twice, because if the system has adaptive behavior, it's complex. And it means behavior is there and it's adaptive. If it is changing according to changes in circumstances, or according to changes in memory. A system is adapting to what's an example, immune system is a functional system. And it is adapting to new pathogens that come in, and it's adaptation in the form of building up a memory in the form of sending out T cells or not sending them out. Any living system is is adapting a flock of birds would adapt if the predator comes in, they would, you know, the flock would, for example, dissolve and then form back again afterwards. Which also means that adaptive behavior is a form of robustness and resilience, because if a system does not adapt, then it's much more vulnerable to perturbation. So the flock of birds or show the fish does not adapt to, you know, shortcoming in, and just all the eating.)
- Time 0:23:10
-

(highlight:: Modularity of the Brain: Resilience and Adaptive Behavior
Key takeaways:
• Modularity of the brain allows for adaptive behavior and resilience to damage.
• If a part of the brain is damaged, other parts can take over and perform the necessary tasks.
• Damage to one part of the brain does not necessarily affect other modules.
• Adaptation occurs on the level of these brain modules, demonstrating extreme resilience to damage.
Transcript:
Speaker 1
Modularity of the brain is also a form of robustness and a form of adaptive behavior. So, if parts of the brain are damaged, then other parts of the brain can take over that are usually not originally not in terms of the function made to perform this particular task. But because the heart of the brain that's supposed to do it has gone down, it's not there anymore. The brain can adapt. And because of the modularity, other parts of the brain are not damaged because they're separated enough. But then the adaptation happens on the level of these modules of the brain, which is an extreme form of resilience, really, to damage.)
- Time 0:25:35
-

(highlight:: The Six Major Products of Complex Systems
Transcript:
Speaker 2
This one is all about the products that come out of complex systems. And they are spontaneous order and self-organization, non-linearity, robustness, nested structure and modularity, history and memory, and adaptive behavior.)
- Time 0:01:47
-

(highlight:: Understanding Spontaneous Order and Self-Organization in Complex Systems
Key takeaways:
• Self-organization is a process that occurs without external control.
• Living systems, such as beehives, exhibit self-organization through division of labor and nest building.
• Chemical reactions demonstrate self-organization through the emergence of structure from a disorganized state.
• Self-organized behavior in immune systems is distributed and not centrally controlled.
Transcript:
Speaker 2
So, let's just jump straight into spontaneous order and self-organization.
Speaker 1
That is probably what captures our interest most of all these features that you've mentioned, Sean. This is what makes them interesting because it's something that's very visual, right? Self-organization. We've spoken about the lack of a central control. So, that's in the word self. The system does it itself without something externally or some central element doing it for it. That's the self. And the organization is that something comes out of nothing. The nothing in this case is what we've spoken about before, so it's the disorders, the feedbacks. So, out of these things, something arises and that is order structure. We had several examples already spoken about in the show and I've mentioned chemical reactions because it's so visual, you have, initially, some liquid which doesn't have any structure To it and then you let it go for a while. And suddenly you see circular forms, you know, circles, colored circles coming out. That is a form of self-organization. Then there are, of course, all the living systems we've spoken about that would be the beehive has a form of self-organization. Initially, a colony starts out small and then you have the division of labor which at some point is organizing itself. You have the nest site that's being built is the form of self-organization.
Speaker 2
And the key bit there is that the individual bees or ants in and of themselves don't really do much. It's only when you put them all together and make them interact that we get this.
Speaker 1
Yes, it's a process, right? So the system starts out in some state which is, if it really starts out, it's a very disorganized state. So in the case of the chemical reactions, initially you have no structure whatsoever, you've just poured the chemicals in. It's at the very beginning. For a beehive, at the very beginning you would have a queen and a small set of workers. There is no nests, there is no division in which bees care for the queen and which bees carry in the food and the water and so on. You could even say in an immune system, the response to a virus initially, the system is in some state which is already ordered, of course, but once the pathogen comes in, then the system Self-organizes the response. And that is not centrally controlled. It is happening in a very distributed, like we've heard explained, a very distributed way. This response is a form of self-organized behavior.)
- Time 0:02:04
-

(highlight:: Non-Linearity in Complex Systems: The Response is not a Linear Function of the Input
Transcript:
Speaker 1
Nonlinearity happens in so many ways and some are more simple, more trivial than others. One form of nonlinearity is this exponential growth that we've heard about. For example, in growth of a virus when it enters a host, then it replicates. And this replication is not that after a day there will be double the amount and after a second day, then there will be just a little bit more than double. That's not how it happens. It will be doubling every day, let's say, or every few hours depending on the virus, which means that the number of viruses that you find is not just the same as the number of days you've Waited, but it is way, way more than that. And this exponential growth happens in, but scaling laws are another example of that form of nonlinear growth. So, especially in terms of time, these systems have a nonlinear change over time.
Speaker 2
Tipping points, they are form of nonlinearity.
Speaker 1
Tipping points are absolutely form of nonlinearity. So, for one, tipping points, the different aspects of tipping points that show this nonlinearity, the most obvious one is, of course, that a tipping point is something where a system Is in the somewhat unstable state, and it keeps being nudged from the outside, which we've heard about before. And a small nudge, if it is away from a tipping point, a small nudge will just cause a small reaction of the system, slight adaptation, slight adjustment, whatever. But when it is close to a tipping point, a small nudge will cause a huge change in the system. So, that is a form of nonlinearity in the sense that the response is not a linear function of the input, and that's particularly strong in tipping points, that's different.)
- Time 0:04:51
-

(highlight:: Robustness in Complex Systems: How resilient the system is to outside disturbances
Key takeaways:
• Robustness is an emergent feature due to conditions like disorder and feedback which make the system robust in the face of small perturbations and damage.
• The interplay between positive feedback and disorder is responsible for the emergence of robustness.
• Decentralized control contributes to the system's ability to survive even when parts are removed.
Transcript:
Speaker 1
Robustness is somehow there in all of these emergent features, but in and of itself, it is emergent, again, because of the conditions, the disorder, the feedback, they are actually Responsible for something to be robust. And the system as a whole is robust in the sense that, you know, small perturbations from the outside and nudge, slight damage to the system. It does not stop the system from functioning or the system from self organizing. It is, in that sense, an emergent feature, so it's a product of the conditions.
Speaker 2
And part of it from, and we obviously talked about it's part of it's from the sort of the interplay between positive feedback trying to put loads of order into the system, and you have Your noise or disorder trying to take away that nice order and it's the tug of war between the two of them. The other point you make that I really enjoy is that you can grab a handful of hands out of the end colony and you don't kill the colony. And that presumably comes back to this concept that it's not centrally controlled. It's all dispersed throughout the system. So taking away a little chunk doesn't disable it. The same as we're carving off a piece of the internet doesn't kill the internet.)
- Time 0:07:07
-

(highlight:: The Difference Between Nested Structure and Modularity in Complex Systems
Key takeaways:
• Nested structure involves zooming in to see multiple levels of structure, while modularity involves separating a system into parts with different functions.
• Democracy is an example of nested structure where decisions are made on multiple levels, from parliament down to local councils.
• Modularity is exemplified in the brain, where different parts are responsible for different functions.
• Structurally, networks can also exhibit modularity.
• Nested structure involves hierarchy, while modularity does not.
Transcript:
Speaker 1
Nested structure means that you zoom in and you see no structure and you zoom in again and you see no structure. And that is even true on a somewhat more abstract level, say a social group. Democracy is one of my favorite examples here, where you have certain decisions that are being made on a very high level, say the parliament. But then you zoom in and you ask, well, how do these parliamentarians get to their power? Well, that because they've been elected by a certain subgroup of people and then you look at that subgroup and you see you have local city councils and you look into the city councils, So on and so forth. So nested structure is that you see at some level a structure you zoom in, you see another one. Modularity is slightly different. It's more to do with function. So modularity means that the system is separated into parts, and these parts take on different functions. The main example is the brain, different parts of the brain, they all consist of neurons and little other bits and bobs, but essentially neurons, and there's parts of the brain that Are responsible for the vision parts of the brain that are responsible for the rotary functions and so on. So modularity is to do with function and it separates the system into subsystems that are somewhat on an equal level. You see that structurally networks networks have been spoken about here, where parts of the network are the brain is a network right and part of the network are responsible for different Things. So that's a form of modularity as well.
Speaker 2
So you see that nested structure is has hierarchy, whereas modularity doesn't. Is that the role solo on the same plane.)
- Time 0:10:27
-

(highlight:: History and Memory in Complex Systems
Key takeaways:
• History and memory are two distinct concepts.
• History refers to the origin and development of a complex system.
• Memory is stored within the complex system and can be older than the elements of the system.
• The brain, immune system, and colonies can all have memory.
• Memory is stored in biological and physical form, and reactivated when necessary.
• Memory is a tool that the system uses to its advantage.
Transcript:
Speaker 2
So history and memory. It's history and memory.
Speaker 1
We like to distinguish between history and memory because history is you can think of the history of a complex system. How did it come about that is, you know, how did if you like any the history of any living complex system goes back to origin of life which goes back to the origin of the universe and so on. So the history is really in a way as far back as we know at the moment. And they all do have history, if nothing else because they come out from these conditions that we've spoken about disorder feedback and so on. The memory is within the complex system. Of course, the brain has memory. And that's what it's for. Remember things we store them in in neural structures in the brain. The immune system also has memory. It remembers pathogens it's seen before, even if it was years and years ago, and it stores that memory in a biological physical form. And it reactivates it whenever it's needed. And colonies can have memory. So the thing about memory, what makes it so interesting is that the memory of a system can be older than the elements of the system, which means. If it has seen a pathogen 10 years ago, there might not be a single T cell. That's the same anymore compared to 10 years ago, but the system has remembered that's memory and that's fascinating. And the same in fact can be true about and colonies they can remember sources of good food from, you know, this is being sort of passed on from generation to generation so even though the Food source was discovered many years ago. And none of the answers that old, but the ancolony as a whole has kept that memory. So memories stored within the system and it is something that the system uses to its benefits.)
- Time 0:16:29
- history, memory, complex_systems, 1todo evernote,

(highlight:: Memory is a Persistence of Structure and Non-Living Systems Can Exhibit It
Transcript:
Speaker 1
We like to state things as general as possible. So memory is something, you know, the way I've spoken about it until now, it's something just more intuitive, I guess. I remember a face or a song or whatever. But memory is in a way a persistence of structure. And the song, if I remember a song, it's a persistence of structure in my brain. But persistence of structure, I can also find a non-living systems. So if you have, for example, Jurassic Coast and South of England comes to mind for some reason, I don't know. It's a beautiful structure. And it has come about through this interaction between, of course, the ocean and the coastline. And it's been there for a long time. It's, you know, slowly changing over time. If you like, it's a way of, it is the memory of these past interactions between the ocean and the coast. And there's no living system involved, not in the way I'm speaking about it. Now it is really just interaction between physical elements. And it is a form of memory because it's persistent structure.)
- Time 0:20:20
-

(highlight:: Adaptive Behavior in Complex Systems
Key takeaways:
• Adaptive behavior is something associated with complex systems that are alive or functional.
• Complex adaptive behavior means the behavior is there and it's adaptive, changing according to changes in circumstances or memory.
• Adaptive behavior is a form of robustness and resilience, making a system less vulnerable to perturbations.
Transcript:
Speaker 2
Adaptive behavior.
Speaker 1
What's that adaptive behavior is certainly something which we would only associate with complex systems that are alive or functional. You often see people talk about complex adaptive behavior, which I think is saying the same thing twice, because if the system has adaptive behavior, it's complex. And it means behavior is there and it's adaptive. If it is changing according to changes in circumstances, or according to changes in memory. A system is adapting to what's an example, immune system is a functional system. And it is adapting to new pathogens that come in, and it's adaptation in the form of building up a memory in the form of sending out T cells or not sending them out. Any living system is is adapting a flock of birds would adapt if the predator comes in, they would, you know, the flock would, for example, dissolve and then form back again afterwards. Which also means that adaptive behavior is a form of robustness and resilience, because if a system does not adapt, then it's much more vulnerable to perturbation. So the flock of birds or show the fish does not adapt to, you know, shortcoming in, and just all the eating.)
- Time 0:23:10
-

(highlight:: Modularity of the Brain: Resilience and Adaptive Behavior
Key takeaways:
• Modularity of the brain allows for adaptive behavior and resilience to damage.
• If a part of the brain is damaged, other parts can take over and perform the necessary tasks.
• Damage to one part of the brain does not necessarily affect other modules.
• Adaptation occurs on the level of these brain modules, demonstrating extreme resilience to damage.
Transcript:
Speaker 1
Modularity of the brain is also a form of robustness and a form of adaptive behavior. So, if parts of the brain are damaged, then other parts of the brain can take over that are usually not originally not in terms of the function made to perform this particular task. But because the heart of the brain that's supposed to do it has gone down, it's not there anymore. The brain can adapt. And because of the modularity, other parts of the brain are not damaged because they're separated enough. But then the adaptation happens on the level of these modules of the brain, which is an extreme form of resilience, really, to damage.)
- Time 0:25:35
-