Interesting stuff!

I'm mostly thinking individual cells in a multicellular organism (i.e. lung cells in a person). It is indeed very hard to understand what they are optimizing for. Obviously, the organism as a whole is under selective pressure, but I'm not sure how much an individual cell in a given organism actually "feels" the pressure. Like, they undergo many cell cycles during one organism's life, but they're not really evolving or being selected during each cell cycle. Of course, this isn't always true as tumors definitely display selective pressure and evolution. But for normal tissue, I prefer to think of cells as dynamical systems operating under energetic and mass flux constraints. They're also constrained by the architecture of the interactions of the genes and proteins in the cell. All that adds up to something that looks a lot like evolutionarily optimized phenotypes, but I think that might be a bit deceptive, as the underlying process is different. It's not at all clear to me though. You're really getting at some deep questions! You might find this paper interesting in that regard:

https://www.nature.com/articles/nmeth.3254

Regarding reducibility and observability of time series, you might also find work from James (Jim) Sethna's lab at Cornell interesting. The math can be a bit hairy, but I think they do a pretty good job at distilling the concepts down so that they're intuitive. The overall idea is that some complex systems have "sloppiness", like some parts of the system can have any kind of weird, noisy behavior, but they don't change the overall behavior that much. Other parts of the system are "rigid", in that their behavior is tightly connected to the overall behavior.

https://arxiv.org/abs/2111.07176v1

You ought to get yourself connected with some folks at the Santa Fe Institute, if you haven't already. I know one affiliated professor, let me know if you want an introduction. At the very least, if you like podcasts, check theirs out. It's called "Complexity" and it's quite good.

To be honest I'm not really sure what advice to give you. You're probably in a spot where your knowledge/perspective is advanced enough to make you impatient around the fundamentals, and at the same time I'm not sure that you have the background required to take full advantage of more advanced materials. You don't seem to be where most 16 year olds are, is what I'm trying to say.

This is especially tricky in the field of bio / biochem, which feels like it requires memorizing a million facts before one gets to do any real thinking and reasoning. This unfortunately tends to filter out a lot of more mathematically-minded people who are stimulated by puzzles, which I think is a shame.

For what it's worth, I really enjoyed this textbook. I'm not sure you will find in it what you're hoping to find, but I hope it sparks even more curiosity; it's fairly advanced, probably more targeted at late-BSc or MSc/PhD students: https://www.amazon.com/First-Course-Systems-Biology/dp/08153...

If you're interested in getting an introduction to cybernetics, theres:

1. Ashby's introduction, but that's from the 60s.

Foundational, but is limited to 1st order cybernetics.

2. E. W. Udo Küppers, A Transdisciplinary Introduction to the World of Cybernetics (2023): https://link.springer.com/book/10.1007/978-3-658-42117-5

Provided a broad picture and basic intro to the history, central concepts, and various involved thinkers involved.

3. Stuart Umpleby's 6 hour lectures on the Fundamentals and History of Cybernetics (2006): https://www.youtube.com/playlist?list=PLB81F4FC0EDC4DECC

Provides a historical overview and introduction to applications of cybernetics in social sciences.

Crucially, Umpleby's history mentions the exact reason why Cybernetics never quite took off in America (well, aside from the fact that it was just difficult to fit into a disciplinary box). Heinz von Foerster, head of the Biological Computer Laboratory, did not want to provide a b.s. military justification for Dept. of Defense funding after the Mansfield Amendment -- (which, was passed in response to student protests of divestment from the Vietnam War).

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.

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.