Indeed, lack of time-series observability makes it harder for us to find general patterns or causal events.
Definitely agree that biology is the pinnacle of all complexity - IMO something like macroeconomics or human behavior within set systems (society, politics, etc.) is fairly reducible to a very small and finite set of incentives that agents optimise for (food, shelter, status, acceptance, etc.).
Given this, Non-linearity and stochasticness still adds up to a general nature of non-determinism for the entire system.
With Biology on the other hand is extremely more complicated to study as - correct me if I'm wrong - it's still hard to realise what agents in systems are optimising for. reduction of free energy? reproduction? general homeostasis? etc. and then all these play varying roles in diff contexts, and then we'll still have to figure out how/why self-assembly and "wholes" emerging from smaller "wholes" (... ad infinitum) actually happens.
Really fuzzy thoughts but I believe There is some merit in exploring reducibility and observability from a time series perspective while considering effects of synchronity/asynchronity of observability and later how much we can desirably steer systems. Really fuzzy but I hope to work on this a bit more.
Thanks a lot for your very interesting comments! Not discouraged at all, love your view on systems theory being a "routine analysis" like statistics, i.e. a very generally applicable layer or meta-science that's an entirely new way to see things, which I should've articulated better in my post.
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:
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.
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.
Thank you so much for the link to those two papers. I'll try and go through them.
>Like, they undergo many cell cycles during one organism's life, but they're not really evolving or being selected during each cell cycle.
This is a really interesting perspective.
>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.
I have read a few posts from SFI faculty and seen some video lectures of Krakauer and others, but as you said, I should get in touch to some degree.
You're very kind and I really appreciate you offering to intro me! I would really love that!
Would you mind if I follow up on this via e-mail? Can I send one to the address mentioned on your Vanderbilt department page?
I think that tool might be just any general framework that gives a better idea of what any small microscopic actions might lead to at a high-level. We definitely cannot qua(nt/l)ify how actions seep through given free-will and a general fringe-ness to us. We can still at least identify most probably scenarios without much difficulty. I believe behavioral economics or even epistemic studies do a good job of identifying general trajectories, by virtue of a fairly high sense of reducibility given human behavior and the benefit of hindsight respectively.
Indeed the human mind by itself isn't really trained to think beyond maybe one or two orders of implications that actions hold. Hindsight and somehow modelling agentic behavior by understanding incentives might do the trick.
Thank you so much for the kind words! I'm definitely a little ignorant with respect to systems biology efforts. I have an okay-ish idea of the work of someone like Uri Alon, it's definitely not enough. What resource would you recommend for me to jump into? Uri Alon's course? I believe I lack many pre-requisites to take it.
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...
>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.
yes, this is exactly the part that makes it really really hard...
Yeah, entropy definitely has been included in some forms of thought that are very correlated with complex systems. Schrodinger early on had a very interesting insight on life and entropy, people like Jeremy England are taking that view forward. Work by England, Crooks, etc. very beautifully relates entropy and the probability of any state x existing more than all others.
The information theory counterpart of entropy seems extremely relevant in describing coordination failures, some forms of stochasticness that aren't necessarily derived from lots of molecules with high degrees of freedoms interacting together. Also might hold high explanatory power in describing why trickle-down/bottom-up and top-down effects are slowly negated and diluted - although I believe this is fuzzy thinking and we need a better tool than just entropy to understand this.
Thanks a lot! SO many interesting recommendations in your comment. Yes, I agree that divergence is a very positive property right now, it might also allow for even more unexpected cross-pollinations and comparative studies as the pool of studies gets bigger.
Yes, I think I agree that just general non-determinism within such systems makes it impossible to "model" them. But, I believe regardless of how stochastic the behaviors are, there are certain properties that the systems might be optimising for. Long way to go for all of us.
Interesting! Have heard about Christopher Alexander's work, but have never really jumped in. Maybe I should do that now.
>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.
Wow! Yes! Agree with this view that all design and organisation is mostly just the most optimal/favorable state for the entire system to be in. What constitutes as favorability might be low free energy, high interconnect, distributedness etc.
May I suggest you to look into the work of Jeremy England in a similar light of self-assembly and optimisation in non-equilibrium states? Some really really interesting takeaways there, me sharing some of my interpretations might constitute as epistemic noise as I'm not sure if I understand each bit of it completely well at a 100%.
There was a great article about him in Quanta, and you might want to check out his talk at Karolinska Institutet.
Thanks for the recommendations, and I'll look out for your talk!
Yes. I'm aware.
I think cybernetics has definitely drifted away from what the original scope was, also I think modern interpretations of cybernetics-ish ideas and complex system studies are slowly also incorporating social sciences and economics and so on.
Interesting to note that if you look for journals on cybernetics, most papers are closer to EE, Deep Learning and some telecommunications here and there, if that constitutes as a good metric of how much the semantic meaning has shifted from its original identity.
If you haven't already I highly recommend reading "Introduction to Cybernetics" by Ashby, it's got the nitty-gritty formalization that later "Second Generation" et. al. cybernetics drifted away from.
> This publication has been made possible largely through Mick Ashby, the author's grandson, who has convinced the copyright holders (the Ashby estate) that they should allow us to produce an electronic version.
While I agree that nitty gritty formalizations are important to grasp, it's been made clear that the formal sciences were often insufficient in facilitating insight on the type of complexity cyberneticians cared about -- especially that of process oriented circular causality, which often involved paradox and self-reference.
> Shannon was like Spencer-Brown a mathematician and electrical engineer. In his study of data transmissions, he has demonstrated how any medium generates background noise that interferes with the transmitted characters. To this day, mathematics has not perceived or not wanted to perceive the elementary consequences of this for mathematics and logic. To this day, mathematics is regarded as a teaching that is independent of the medium in which it is written and through which it is transmitted. Nobody can imagine that the medium could have an influence on the signs and their statements. Mathematics is regarded as a teaching that is developed in a basically motionless mind.
Having taken the last 2 years to really go through the discourse surrounding second order cybernetics beyond Ashby's introduction and Stafford Beer, I learned of a pivotal text called Laws of Form, which was at the heart of second order cybernetics. The formal system was directly incorporated in Varela and Maturana's thesis of autopoiesis, and Niklas Luhmann was also /obsessed/ with Laws of Form for much of his academic career. This is a progenitor of our current interest of enaction and embodied cognition!
With the book's 50th anniversary in 2019, the discourse has been seeing a rejuvenation thanks to some small conferences at https://lof50.com. I've seen some intriguing applications. Some are a bit far out, but that's the nature of systems thinkers, yeah?
A couple that may be of interest:
William Bricken's work on Iconic Mathematics, a system that covers K-12 math and bridges it to purely physical manipulation, shedding matters of complexity difficult that fuel general mathphobia such as: associativity, commutativity, division by 0, bases, functions, order of operations, the disambiguated meaning of equality. Instead, everything is a /structure/.
Bricken's work on computational implementations of Iconic Logic. One example includes a novel SAT algorithm / tautology verification algorithm called Virtual Insertion, which makes extensive use of the notion of semipermeable boundaries, in which the context of a boundary still pervades its content.
Gitta and Ralf Peyn on FORMWELT, a yet-released system aiming to facilitate precise, clear communication of nebulous natural language concepts through the use of injunction and self reference.
>While I agree that nitty gritty formalizations are important to grasp, it's been made clear that the formal sciences were often insufficient in facilitating insight on the type of complexity cyberneticians cared about -- especially that of process oriented circular causality, which often involved paradox and self-reference.
I wholeheartedly agree. Hence why I think we are dealing with an entirely new type of science, the basic principles and theorems are yet to be discovered.
Lots of interesting pointers and links throughout. Thanks again!
I would say that the first-order Cybernetics (as exemplified IMO in Ashby's book) is all about symbolic formalism for "circular loops in causality", and that Second-Order Cybernetics is a species of mysticism (I hasten to add that I don't mean that in a derogatory way. I'm a Mystic myself.)
You could imagine a spectrum from logic to cybernetics to philosophy to mysticism. It's all fine, just I believe that it's important to be clear where on the spectrum you're working. If you want to build machines that do things use Cybernetics and feedback/control theory, if you want to grok reality and self eat a mushroom and read "Gödel, Escher, Bach" or Tao Te Ching.
In re: "Laws of Form", yeah, he identifies the boundary or distinction between the mystic realm (non-form, non-distinct, non-dual) and symbolic logic, and then builds a lovely binary Boolean logic directly off of that. It's a tour de force.
The really interesting thing is that George Spencer-Brown figured out how to deal with circular logical systems by introducing the concept of imaginary Boolean values.
(That third rule in the calculus, discovered by Bricken, is the kicker!)
cf. "The Markable Mark" George Burnett-Stuart
http://www.markability.net/
GBS (not GSB, they're two different people) has managed to extend the system to Predicate Logic as well!
To sum up, we need symbolic formalism to communicate and build machines, otherwise we're just sort of reading poetry to each other, which can still be helpful, but in a different way than building machines. (And when I say machines in the context of Cybernetics I mean to include those made out of people! "Human use of Human Beings", eh?)
As an aside, there is a fascinating talk and book "My Stroke of Insight: A Brain Scientistʼs Personal Journey" by Dr. Jill Bolte Taylor:
> In it, she tells of her experience in 1996 of having a stroke in her left hemisphere and how the human brain creates our perception of reality and includes tips about how Dr. Taylor rebuilt her own brain from the inside out.
When "Laws of Form" talks about the beginning of logic from the pre-logical non-distinct or non-distinguished realm, the "mark" that divides the world into A and Not-A, it turns out to be quite literal, purely biological: the brain does it. When the part of her brain that "does logic" was rendered inoperative due to the stoke she was having, she reports an inability to tell herself from the world around her accompanied by oceanic bliss...
Mysticism is real, you just can't talk about it. The very first chapter of the Tao Te Ching says it right off: the Tao that can be talked about is not the Tao.
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).
Huge thanks for the list! Interesting to wonder just how influential or generally just of what nature cybernetics would be today without funding issues, lack of categorisability and the field slowly drifting away from the original vision Wiener had.
Absolutely.
Broadly, I wonder what leads to schools not adopting emerging fields as part of the formal curriculum. Interesting to note even in 2021, only 51% US k12 high schools were found to have a CS course. Does not seem like a capital problem to me. Is this just inertia or a legibility problem?
As with any monopoly, the incentives for public school administrators are all out of wack. Adding a CS curricula takes real time and effort (lost summer vacation time, effort required to convince the board/PTA, picking a curriculum, hiring teachers for an unfamiliar topic). It brings with it real risks and headaches (budget issues, vulnerability/ignorance in a new domain, possible failure/embarrassment, board/PTA conflict, dissatisfied students/parents). Meanwhile the benefits are not tangible and the cost of not implementing a new CS curriculum is zero.
For public school administrators (as with all process owners) it's far easier to simply repeat what they did last year.
Oof yeah. The legibility-gained per effort put in for most admins working in a system that inherently incentivises tangibility and observable "utility" (whatever that may be in this case) reduces any hope of seeing much change.
Maybe this is another good problem that Systems Sciences might hold a great explanation too :-O.
Thank you for your very interesting comment and the reading recommendation.
I agree with your general sentiment that chasing "wide applicability" or trying to force a narrative that xyz theory will explain xyz might be hugely detrimental.
I agree my post and many discussions about complex systems, specifically one in an evangelic-type light might be over-optimistic.
We definitely must approach all work on such a theory with careful attempts not to overhype it. My post was an attempt to lay out some interesting possibilities.
We must remain optimistic anyway but I will be more careful in this regard going forward. Thanks again.
Really like your thoughts!
Indeed, lack of time-series observability makes it harder for us to find general patterns or causal events.
Definitely agree that biology is the pinnacle of all complexity - IMO something like macroeconomics or human behavior within set systems (society, politics, etc.) is fairly reducible to a very small and finite set of incentives that agents optimise for (food, shelter, status, acceptance, etc.).
Given this, Non-linearity and stochasticness still adds up to a general nature of non-determinism for the entire system.
With Biology on the other hand is extremely more complicated to study as - correct me if I'm wrong - it's still hard to realise what agents in systems are optimising for. reduction of free energy? reproduction? general homeostasis? etc. and then all these play varying roles in diff contexts, and then we'll still have to figure out how/why self-assembly and "wholes" emerging from smaller "wholes" (... ad infinitum) actually happens.
Really fuzzy thoughts but I believe There is some merit in exploring reducibility and observability from a time series perspective while considering effects of synchronity/asynchronity of observability and later how much we can desirably steer systems. Really fuzzy but I hope to work on this a bit more.
Thanks a lot for your very interesting comments! Not discouraged at all, love your view on systems theory being a "routine analysis" like statistics, i.e. a very generally applicable layer or meta-science that's an entirely new way to see things, which I should've articulated better in my post.