We must seek a widely-applicable Science of Systems

Having studied complexity from a computational perspective (via Santa Fe Institute and 1st wave Cybernetics) and a natural sciences one (via Dave Snowden and Alicia Juarrero) my preference is to stay away from modelling complex systems particularly complex adaptive ones. There is value in modelling, but heed the advice that all models are wrong. If you want to understand why, take a look at Steven Wolfram's Computational Irreducibility and Dave Snowden's Cynefin framework.

As for your interest in self-assembly and emergence I would highly recommend Alicia Juarrero's Dynamics in Action and Context Changes Everything - they are both tapping biological sciences to update and better inform our views of the world in deeply meaningful ways. The former changes our notion of cause-and-effect as the driving force in complex systems, stepping away from the Newtonian billiard ball frame. The latter expands on it talking about how constraints underpin the actions and dynamics in complex systems.

I'd agree that I'd love to see some convergence eventually in the complexity sciences world - but it is a new science relatively speaking - the divergence is a positive property in my opinion!

Keep up the energy, keep writing and keep researching! I enjoyed your post, it reminded me of the excitement I have for the field as a whole and the thirst I had for very similar questions! I wouldn't of guessed you were a 16yr old had you not stated it. Be prepared to have fundamental views changed and get comfortable with uncertainty!

My PhD thesis was about the extension of smooth functions. In the 1960s, ideas in this area were studied under the umbrella of ideals of smooth functions, and had applications to catastrophe theory. So I spent some time reading about this topic. If you want a reading recommendation, the book "Differentiable Germs and Catastrophes" I remember being good, as well as "Stable Mappings and their Singularities".

I bring this up because I believe that at the time catastrophe theory was seen as a "widely-applicable science of systems". Or at least some practitioners tried to sell it as such. This point of view eventually soured to the detriment of catastrophe theory, which cleared out. I don't think this was a good thing: catastrophe theory (the study of the singularities of smooth maps and their consequences to dynamical systems) is an interesting topic with many remaining open questions. But it was seen as cringe that people were, e.g., using Whitney's classification of the generic singularities of planar maps to try to say something about predator/prey dynamics or whatever. Any claim about applications of catastrophe theory was infected with this stink, and so people lost interest in it.

I wonder if you're looking for cybernetics? The original meaning from the 1940s, not the corrupted science fiction shibboleth. Wikipedia - "The initial focus of cybernetics was on parallels between regulatory feedback processes in biological and technological systems...Wiener introduced the neologism cybernetics to denote the study of 'teleological mechanisms'."

Wikipedia suggests it lost a lot of drive in part because AI and computer science split off from it.

To me, Christopher Alexander's work comes closest to describing "systems science". I recommend Notes on the Synthesis of Form, The Timeless Way of Building, and then skipping to the Nature of Order series.

I'm of the opinion right now that what we call "design" and "architecture" is really just the science of finding stable habitable zones in high-dimensional problem spaces.

What's cool about Alexander's work is that he makes a great case that this stuff is objective phenomena that can be studied!

I'm planning to write much more about Christopher Alexander on my own blog in the future, but meanwhile I can recommend Dorian Taylor's excellent works:

• https://the.natureof.software

• https://doriantaylor.com

I gave a talk on this subject at DDD Europe this year, so keep your eyes out for "Timeless Way of Software - Taylor Troesh" on their YouTube channel :)

• https://www.youtube.com/@ddd_eu

Somewhat related, I feel like the book Thinking in Systems should be taught in high school

https://www.goodreads.com/book/show/3828902

It would be very useful to have an inheritance system to feed outputs of scientific theories into other theories. Just like how computer programs can access code from included libraries.

Chiara Marletto and David Deutch developped such a system, called constructor theory. It is build up from constructors, which are like little computer programs that describe what they refer to as different "tasks". And these tasks are counterfactual operations.

> How does the body react to imbalances in some internally-relevant biomarkers?

How systems regulate themselves (and also perpetuate themselves) is the question behind cybernetics, and in the organisational context, management cybernetics. The problem generalises way beyond biology. The information theoretic and control implications are fascinating.

(I’m writing a book on the subject; ping me if interested)

There is an approach that I like and I think allows one to compress quite a few different description models from different domains. Take a look at this image from wikipedia: https://commons.wikimedia.org/wiki/File:Systematik-Philosoph... You see "Theoretische" and "Praktische" philosophy in the rectangle with a diagonal which probably could mean that you can sort something based on the relation between matter and information, where something is more practical and less theoretical (say 30% practice and 70% theory) add a stimulus-response diagram at the bottom and various information-material circuits inside that allow you to show how something is transformed.

There is an development of this idea from some author which leads to something like https://imgur.com/a/AmF7AJe and currently the author tries to find the connection between syllogistics, Boolean algebra, Euler-Venn diagrams, and more. You can take a look at https://www.youtube.com/@Syllogist/videos Many of the recent videos have English subtitles It's hard to describe the whole idea at once, but maybe someone will have the courage to learn something from it.

my philosophical take is this all revolves around what constitues "one system"

on one level, something is a subsystem of a larger supersystem

on another, it's all the one and only system. but why wouldn't the components be systems in their own right?

and sure, it's all about the 'appropiate' level of abstraction. but my point is that any "science of systems" must give a working theory of levels; or at least say something on how to grapple with this. it's not sufficient to leave it as "that aspect is an art"

Seek we must, but will we find something?

Complexity science is the major remaining terra-incognita of our era. The allure of seeking to break into such a genuinely new domain is strong. The intellectual (and not only) rewards would obviously be beyond compare. The dimensional extremes probed by "standard" micro and macro physics are increasingly into diminishing returns. Thousands of people, gargantuan budgets and devices etc. but in a macro sense, rather disappointing progress: Our mental toolkit and understanding of the world in 2024 is not that different from that the Einstein/Bohr era circa 1924. It has been an era of fleshing out the details, magnificent and more productive than any previous period of history, but it saturated without turning things upside-down.

All the while, complexity is all around us, even inside us. Mysterious, defying attempts at description, let alone explanation. One can setup experiments for next to nothing. Complexity is very "accessible". So why is it still a sketch of field rather than an actual field?

If the constraints are not external then they must be internal (cognitive limitations, blind spots etc). For sure we lack mathematical tools. But maybe we lack even an adequate set of relevant pre-mathematical notions, these vague but powerful concepts that precede the sharper analytical tools and elaborate equations.

One think is for sure: Very smart people have tried very hard and if you are going to see further you must (at least) climb on their shoulders :-)

Great article :). You definitely will be going places.

  why everything exists in a holonic sense i.e. a "whole" in its own is composed of many wholes themselves, and goes on to partake in a bigger "whole".

You’re gonna love philosophy!! This is covered most definitively and scientifically by Hegel’s Science of Logic, but that’s like super advanced high level philosophy so you might not want to start there lol. Either way best of luck, I totally agree with your general thesis! You’ll be happy to know that, in general, this has already been solved by Kant, Hegel’s idol - even tho people have forgotten in the meantime.

http://www.autodidactproject.org/quote/kant_CPR_architectoni...

http://staffweb.hkbu.edu.hk/ppp/ksp1/toc.html

I’m writing a book on all this atm, so feel free to hmu anytime if you want someone to bounce ideas off of! It’s a profitable time to be a philosopher of science, that’s for sure

The Open University runs a Master's program in systems thinking (which I'm currently studying). There's a free primer course called 'Mastering systems Thinking in Practice' that gives a good overview and is full of references for further reading in the field: https://www.open.edu/openlearn/science-maths-technology/mast...

There's also a developing community at https://www.systemsinnovation.network/, where there are also many (subscription) resources.

The articles, books, and guides available (free) at https://thesystemsthinker.com/ are also worth a look. This mostly pertains to system dynamics rather than any other traditions, but it's a great resource for understanding complexity.

Norbert Wiener had this all figured out 70 years ago - everything old is new again!

I would recommend reading:

Complexity by M. Waldrop https://commoncog.com/learning-from-waldrop-complexity/

The Systems Bible by J. Gall (This one is an odd one but it is good for developing a sense of humor) https://novelinvestor.com/notes/systemantics-how-systems-wor...

This is a wonderful post and articulates something I've also struggled with over the years - and I'm much older than 16!

To me, it can be distilled down to human decision making... how flawed we are in terms of cause/effect, how logical fallacies are so powerful. Ultimately we discovered that the Scientific Method was a tool for us to overcome these flaws. Hopefully there is a similar tool out there in the ether which can help us to navigate complexity with similar confidence.

Great post, you're clearly on the right track. I totally agree that there is a major gap in modern theoretical understanding of how and why complex systems emerge. Breakthroughs in understanding the physical/informational processes that underlie complex adaptive systems could be immensely useful.

I'll add a word of caution though. I'm most familiar with systems theory applied to biology. Biology is, in my opinion, the pinnacle of complexity. However, it's less well acknowledged that it's also very, very complicated. This is important because it means that we have very incomplete knowledge of the base components of any biological system. Like we still don't really know the basic biochemical function of most proteins. Hell, we only just got a partial view of what most proteins even look like (in isolation) via AlphaFold. Measuring the number of all of the proteins in a single cell is effectively impossible with current and near future technology. Any feasible solution for this would probably be destructive, meaning that true time-series measurements are also impossible. These details of what we know and what we can (or can't) observe matter quite a lot, not only because they are the sort of raw matter of a systems theory, but also because they are the levers that we have to use to manipulate the system. There are only about 1000 proteins that we know how to reliably bind molecules to. There are (probably, we're not sure) more than 50k different proteins, if we include isoforms. So, all that to say, we have very incomplete knowledge of biology and very incomplete control of cellular behavior.

This isn't meant to discourage you! Instead, I think there's a tremendous opportunity for systems theory to be really useful (especially in biology) if it becomes a practical, routine analysis like statistics. But, for that to happen, we have to keep in mind the limitations and specific details of the system we're dealing with.

TLDR; we need more research into game theory

I totally agree; it all boils down to math. Linear algebra formed the foundation of a lot of what we have achieved today, including computer simulations and AI, but now society is demanding problems that aren't based in linear algebra but in game theory, as the author describes. So we need to study game theory, that's what the next period of accelerated advancement will be based on

This is an incredible perspective coming from a 16 y/o.

For what it’s worth, it took me spending 12+ years studying biochem and adjacent topics at university, to reach a very similar perspective.

The one criticism I’d make here (and tbh it’s unfair to expect more from the author) is that there has been a lot of work done towards this already. There are many systems biology textbooks, a much greater number of systems papers, and even entire journals on the subject. So I would reframe the observations slightly: there is a lot of prior work, and we need to double down on it and cross-pollinate it more.