Complex Systems from the Eyes of a Hopeless Romantic
When I first saw the complexity science diagram, the first image that popped into my head was the Character Map from Pride and Prejudice. The map shows the relationship of each character, which is arguably the essential aspect of the story. Without emphasizing the relationships, the book would be a collection of random people’s random facts and hard-to-understand words. The book was the first thing that popped into my head as it is my favorite book and the first book I reported on in college. Also, it was just Valentine’s Day, and I spent it alone. Again.
It seems that there is no concrete definition of what a Complex system is. Starting with this information made me feel like Mr. Bennet when he said, “I have not the pleasure of understanding you.” However, based on my readings, there are six key concepts when looking into a complex system: Systems, Complexity, Networks, Nonlinearity, Emergence, and Adaptation.
A System is a collection of entities and their relationships that form a whole. Systems are said to have their characteristics based on the environment it is found in and the environment they create. The most common example used is the body. Different cells with their specific functions form tissues that, in turn, form organs that form a body. From a more literary perspective, a System is a story. Each story is unique based on how the characters act, like sequels with the same cast of characters. It’s a sequel because the actions and environment are different. And that difference in the acts leads us to the next concept: Complexity.
Complexity is when we cannot easily infer behavior from their properties. People are complex. One can never know what the person might do at any given moment. We can have studies to explain why they did it, like clinical psychology, or studies that may predict what they will do, like sports analytics. However, there is no 100% chance of understanding all the factors or getting the right prediction. But I believe unpredictability is the spice of life. Yet, I’m not into super spicy food. So, there must be a way to study this. One way is by looking at Networks.
Networks are the relationship between entities or individuals in a system. “Tell me who your friends are; I’ll tell you who you are.” I think this quote is better than “Birds of the same feather flock together.” The latter has a more logical basis in the context of a system. In a group of people, specific roles arise. With these roles, official or unofficial, acts occur that affect everyone, inside or outside the network. Although there is a hierarchical notion when talking about Systems within Systems, i.e., the heart a subsystem of the cardiovascular system or the cardiovascular system a subsystem of the human body, there is none for mutually exclusive Systems. Now, the concept of Nonlinearity comes into play.
The standard visualization for Nonlinearity is the speck of dust snowballing into a boulder. However, I like to visualize it more as cancer that affects the other parts of the organism if left untreated. When it comes to Complex Systems, Nonlinearity shouldn’t only be in terms of scale but also in terms of direction. As mentioned previously, relationships are essential, whether it comes in David and Goliath or Romeo and Juliet. Sometimes you can’t choose who you affect. We now go to the penultimate concept, Emergence.
One of the most baffling and complex things about Complex Science is the spontaneous and self-organizing Emergence concept. When I was a student at the University of the Philippines College of Law, a case will always come up during valentine’s day, Chua Qua v. Clave. A teacher from Bacolod fell in love and entered into a relationship with her student 15 years her junior. She was found innocent from immorality with the now famous ruling that included this line by Justice Regalado. “If the two eventually fell in love, despite the disparity in their ages and academic levels, this only lends substance to the truism that the heart has reasons of its own which reason does not know.” In addition to the volume of factors, there are those that we don’t even see. The system that took form in the relationship mentioned above was a System that was baffling to almost everyone who witnessed it.
The last concept is Adaptation. These systems will be for naught if they don’t persist. The couple mentioned above were married in 1975, and they are still married today, with a friend of mine meeting them at a party last 2015. There are so many theoretical parameters that might tell us if a system will or will not work, but nothing beats results and physical proof.
Going back to Pride and Prejudice, it has all the elements mentioned. We have the story’s system with the characters and their actions, which carry nonlinear consequences. We also see their relationships, which are were quite complex. These elements have propelled the story so well that it is still relevant over 200 years in the future. As a future Data Science Leader, I understand that this is still just surface level, and there are even more things to learn in Network Science. But that’s how relationships usually start. If we find ourselves in a sustainable and healthy one, it is a journey of growth. I, for one, am extremely excited to start this journey it may be long and arduous, but as Elizabeth Bennet once “The distance is nothing when one has a motive.”
References
[i] Austen, Jane. Pride and Prejudice. Routledge, 1994.
[ii] What is a Complex System? [Video file]. (2017, May 6). Retrieved from https://www.youtube.com/watch?v=vp8v2Udd_PM
[iii] Gaia. (n.d.). COMPLEXITY SCIENCE. Retrieved from http://environment-ecology.com/general-systems-theory/548-complexity-science.html
[iv] Bar-Yam, Yaneer (2002). “General Features of Complex Systems” (PDF). Encyclopedia of Life Support Systems. Retrieved 16 September 2014.
[v] Taylor Pearson. “Complexity Science — A Basic Explanation (with Examples and Resources).” Taylor Pearson, 30 July 2019, taylorpearson.me/complexity-science/.
[vi] S. V. Buldyrev; R. Parshani; G. Paul; H. E. Stanley; S. Havlin (2010). “Catastrophic cascade of failures in interdependent networks”. Nature. 464 (7291): 1025–8. arXiv:0907.1182. Bibcode:2010Natur.464.1025B. doi:10.1038/nature08932. PMID 20393559. S2CID 1836955.
[vii] Phelan, S. E. (2001). What Is Complexity Science, Really? Emergence, 3(1), 120–136. doi:10.1207/s15327000em0301_08
[viii] Chua-Qua v. Clave, G.R. №49549 (August 30, 1990)
[ix] Gaia. (n.d.). COMPLEXITY SCIENCE. Retrieved from http://environment-ecology.com/general-systems-theory/548-complexity-science.html
[x] Myers, Scott. “Character Maps.” Medium, Go Into The Story, 27 Oct. 2016, gointothestory.blcklst.com/character-maps-7ea6b87d0f3d.
