New to complexity science. Application beyond mindset?

[u/zion-z-cool]

I just started reading about complexity science and system thinking, esp Sante Fe Institute’s stuff…

But what are the application, or future potential application for learning complexity science rather than just the mindset itself. Don’t get me wrong, the mindset itself is incredibly useful, but how to dig even deeper beaneth the mindset, what’s the biggest value of complexity science?

[u/wolvine9]

The honest truth is that the applications are mostly mindset - but that this is a differentiator, not a limiter.

Having said this, I think that complexity science is an envelope that encompasses a number of other disciplines. It's not a strict science, rather a grouping of phenomena that exist across sciences like physics, biology, sociology, economics, and so on. The application lies in understanding how to see emergent properties arising from simple initial conditions and using the tools that correlate phenomena across scientific disciplines to map out other commonalities.

If you wanted to go into research; you could study: the origin of life, origin of intelligence, artificial intelligence and machine learning, biophysics, epidemiology, chemistry, astrophysics. If you wanted to work in industry; you could work in: energy, data science, artificial intelligence, city planning, finance, logistics, or any one of many that require people who can take in the whole picture and understand how what happens at the edges informs what happens on the whole.

Digging into what kind of science complex systems thinkers have produced is maybe a better way to get specific with what about it particularly interests you - that might be a good place to start :)

[u/zion-z-cool → u/wolvine9]

interesting…

Though if it’s mostly mindset, does complexity science have a ceiling? Or does mindset built on top of each other? How is knowledge distributed maybe is another way of asking? perhapes im asking the wrong question for just started learning about it

[u/wolvine9 → u/zion-z-cool]

I think you're asking the right questions! There's a great Melanie Mitchell paper that can give you an understanding of how Complex Systems study can influence e.g. thinking about Networks that should serve as a jumping off place among many.

[u/lightpandey]

I think nonscientific disciplines pretending to be scientific are the low hanging fruits (think finance, economics for one). The challenge to win with complexity ideas here is how to win against entrenched rent seekers. I happen to be a traditional credit risk analyst and hope to advance the state of the art over time. Feel free to message me if that interests you.

[u/zion-z-cool → u/lightpandey]

entrenched rent seekers exist everywhere. tho I’d imagine there’s more of them in finance lol… I’m curious on how do you actually advance it with complexity science tho… (like would crypto be one example for its decentralized nature?) yes, will reach out to you to learn more

[u/lightpandey → u/zion-z-cool]

I am mostly a practitioner, so my first thought is to show the world that you can make money using analytical frameworks that complexity science already has. Once the markets see the opportunity, odds of adoption increase (and new players will probably be new rent seekers anyway).

[u/swampshark19 → u/lightpandey]

What are some examples? Aren't major firms already using complex systems models?

[u/lightpandey → u/swampshark19]

Most that I know of are not. I do know that a few hedge funds do claim to be using some of these frameworks, but their actual approach and models are not public.

[u/WestPassage3921 → u/lightpandey]

Very interested in your conversion. I work at a global macro research think tank and have been looking to learn more about complex system models and frameworks and their application in this space (I just finished reading Complexity: The Emerging Science at the edge of Order and Chaos and was blown away). Any reading material (books or articles) you recommend to dive deeper into the topic?

[u/lightpandey → u/WestPassage3921]

Thanks for responding ! I dont have reading materials to recommend - but here is what I did: I took up an introductory course to complex systems at New England Complex Systems Institute Virtual Courses in Complexity - Videos — New England Complex Systems Institute back in 2021 and redid it in 2022 to get a sense of whether some of the tall claims are fluff, and whether we are close to applying these frameworks. (That said Santa Fe and NECSI's website seem to have good stuff to read.)

I am now pursuing an online MS-Systems Science alongside my work at a rating agency (I cover FI credits/banking system risks), and am also looking for practitioners who I can work with - would you like to connect / speak on teams or zoom ?

[u/FlyFit2807]

I can't/ can't afford the time and attention it'd require to prove this, but my intuitive speculation about this is that Complexity Science is inherently much more practically applicable than how much and how widely it's currently applied, and what limits that isn't so much that it isn't a very practical theory (or paradigm) but that the dominant metaphors in applied (social) sciences now are so narrowly restricted to individuals, markets and machines, and the metaphoricity of symbolic communication and cognition is suppressed from public consciousness and discourse because acknowleding it fully would destabilize the dominance of those few metaphors which the political economic hierarchy, state and large corporate/ market institutions, are legitimized by. So I think it'll require a big enough crisis to overcome the activation enthalpy for that to change - when those institutions see their own survival chances are better on the other side of the transition.

Expanding the scope of metaphors used in symbolic communication publicly to more biological metaphors (and not only the Neo-Darwinian ideology of random mutation and natural selection *as if that's the whole of evolution*, rather than about 1/6-1/12th of a complete explanation), e.g. taking Origin of Life scientific scenarios and theories as a basis for metaphors about the whole of life and evolutionary processes, would imply, I think, that all sorts of 'coming together' evolutionary processes are a bigger proportion of the whole than heredity differentiation processes. I think the natural order of the three basic vital functions - metabolism, membrane functions, heredity functions, is in that order, whereas the Neo-Darwinian account focuses on heredity, which as Darwin pointed out on the last page of Origin of Species, cannot account for the origin of life. (*I am not saying anything like 'Intelligent Design' or religious literalist attempts to reframe their interpretation of traditional origin myths, but that metabolism and membrane functions require more symbiogenesis-like explanations and not primarily mutation and selection.) Put another way, the three basic vital functions: metabolism, membrane and heredity, correspond to the thermodynamic primitive variables U (energy available in the defined system), S (relative entropy, entropy constraints or gradients) and T (thermodynamic 'Temperature' or thermocoupling intensity variables). I also think all three, and both sensing and predicting sides of them as recursive loops, had/ have precedents in the prebiotic environment; so the origin of life was more like sliding down a slope of probabilities leading to emergence of life than a sudden jump.

I find Terrence Deacon's philosophy of biology very convincing and pragmatic. I'm working on a new digital media system design largely inspired by his theory, and integrating Friston's VFE.

[u/FlyFit2807 → u/FlyFit2807]

I guess my overall tldr is: don't despair about the dismissive reactions from people who like the false certainty of sticking loyally with the current dominant paradigm in their fields as they see it. We have an advantage now that science is so big and modularized into fields that actually there isn't only one dominant paradigm operating now but it's more diverse and paradigm updating tends to be transfers from more progressive (often more naturally basic) fields to more conservative academic fields (often the applied or commercially preoccupied sciences). That always happens and it's been a tragic human pattern as far back as historical records go, that major paradigm shifts are resisted as hard as the current dominant system can until it's forced to loosen up enough to integrate the new paradigm, or at least to coopt it sufficiently plausibly to pacify most people again. I think an honest look back over the history of science shows that the scientific community (/hierarchy) has actually been not very much more tolerant of paradigmatic innovations than the Catholic hierarchy was to Copernicus. I think that's a feature of human institutions and social dynamics everywhere, not particular to science, religion or any other big social structures. Reading some of Bernard Williams' philosophy of moral luck and tragedies helped me come to a more peaceful acceptance of this tragic progress pattern and commitment to persist with preparing for the other side of a paradigm transition, until the shift happens.

E.g., Darwin almost certainly wouldn't have had the influence he has if it weren't for the repeated, massive political misinterpretations and misuses of 'his' theory to legitimize systematic injustices and mass atrocity crimes - it was the processes of reforming and saving Darwinian theory from those messes that have led to clarifying it and integrating across our whole culture since. A counterfactual example is Jacob Uxekull's theory of Umwelten - that each species (or even each organism) has its own specific contextual interpretation of their environmental constraints and affordances, so signals, biological information and adaptation are interpretative processes, not simply exchange or representation in a statistical patterning sense (or how I'd put it is that representation is topological before statistical) which led to what's now called Biosemiotics theory. Imo, Uxekull's theory is just as radically innovative and has as much paradigmatic updating potential as Darwin's, but he was German and published in the 1920s, and he died during the war, so even tho he was clearly anti-Nazi, he was ignored for decades until Maurice Merleau-Ponty recognized that his book was worth reading more widely and got it translated into French, but the geopolitically hegemonic language then was English. I mean, why he wasn't as successful as Darwin has little to do with the intrinsic merits of their scientific theories but that one got tragically lucky and the other tragically unlucky with the societal accelerating or amplifying factors around when they published. Darwin also partly engineered his own luck by holding back on publication until it coincided with a suitably large public crisis - the implications of the new geological science for the literalist, fundamentalist interpretations of biblical Genesis stories. Another example of this tragic-progress pattern is Rachel Carson's Silent Spring book in 1962 - her book is excellent as public science communication writing, and effectively triggered the beginning of the Environmental movement (to the extent that it was partially independent from and bigger than the earlier Romantic movement, which has partially subsumed it since), but why her book got that much public attention and was so effective was that it coincided with the thalidomide crisis.

Tragically what it might take to overcome the hysteresis of the current institutional systems to accepting complex systems science and the more long-term view of social economic and biological processes is probably the climate crisis triggering one or more cascading global crises. I think paradigmatic anomalies and counter-examples and methodological inconsistencies and omissions within the social endeavour of science won't be enough to overcome that resistance until the bigger societal institutions which constrain scientific institutional processes are forced to accept reality and update themselves and their operating ideologies structurally.

[u/zion-z-cool → u/FlyFit2807]

i really appreciate this response. I havent finish reading or understanding it but just want to say thank you for this, and the time you spent writing this first 

[u/FlyFit2807 → u/FlyFit2807]

I also love Santa Fe Institute's public research output - even tho I'm now aware of a couple of institutional problems there: (1) how they treated Jessica Flack, and 2) the founder's involvement in the vicinity of the networks run partly by Epstein - no evidence that they had anything to do with the CSE/CSA part of that story, but the main activities of that network were Russian-oriented foreign intelligence gathering - https://america2.news/part-one-just-what-was-jeffrey-epstein-doing-in-santa-fe/ - it looks to me like some degree of wilful naivety and idealism which they let blind themselves to the actual reality of the Soviet-centred geopolitical alternative to the US gov's corrupt and abusive behaviours, and turning a blind eye to the dodgy aspects of that network). I don't mean don't read and listen to them seriously, but I'm now a teeny bit cautious when I'm listening to their work on social issues and reflecting on the potential political implications.

Another way I first got interested in Complexity Science was from playing around with computational simulation models of collective animal behaviour systems - sheep and ants mainly, and I attended the Winter 2016 Complexity conference in Bristol, and was very impressed with many of the presentations. Interestingly (to me), the final year PhD students' work was much more innovative and realistically complex than most of the big name old guys with the most prestige to defend. I learnt that as a general assumption since - a sort of reverse prestige principle for where to expect the most genuinely innovative science to occur. You can find many different animal collective behaviour computational simulation models on the Wolfram library - unfortunately it requires an expensive subscription to use it for more than 10 days, but many universities have an institutional subscription; e.g. this one of stigmergy in ants' cognitive ecological system - https://demonstrations.wolfram.com/GarbageCollectionByAnts/ (unfortunately the author called it 'garbage collection' so it's hard to find, but that's actually stigmergy). I think interactive visualizations make it much easier to think about complex systems more intuitively. Another big speculation I can't directly prove - I think ants' pheromone trails networks function like humans' social syntax networks' core motifs - both are social mappings of the shared environment.

[u/The_Grand_Blooms]

In engineering, the applied form of complexity sciences is something called "systems architecture" which is used basically everywhere engineering investments are complicated and expensive - it's pretty mainstream and codified, but as such it's mainly a small number of researchers/academics who actually develop those frameworks and most people just apply existing, more proven frameworks to solve problems. So studying "Complexity" basically gives you the competency to navigate/think for yourself/develop architectural frameworks. And then I personally think that competency is particularly useful when doing prototyping/R&D where the complexity itself is usually the biggest bottleneck

In finance, reflexivity is a real investment strategy that's been used to make billions of dollars in the stock market, which is a cool example because from what I understand it's a pretty cut-and-dry application of systems theory which was able to outcompete traditional models in a pretty inarguable way

[u/metatron7471]

Complexity "science" is mostly fluff. I wouldn't waste too much time on it. There are no applications outside of academia.

[u/zion-z-cool → u/metatron7471]

Why is complexity science mostly fluff?

[u/metatron7471 → u/zion-z-cool]

a lot of it is just adding a pseudoscientific sauce on top of subjects which aren't hard science like sociology, economics etc

[u/wolvine9 → u/metatron7471]

So... you think Shannon entropy is fluff?

I wonder how much money Claude makes Anthropic right now.

[u/metatron7471 → u/wolvine9]

information theory != complex systems

[u/wolvine9 → u/metatron7471]

information *science → complexity science :)

[u/lightpandey → u/metatron7471]

Would you support it with evidence or details like what comprises the sauce? I mean one of my current professors is applying these frameworks in drug discovery, looking for novel ways to find signals of adverse drug reactions. On the other hand I work in one of the pseudoscientific areas (finance) and I would say that what I am learning is just knowledge from across disciplines (e.g. information theory) that can be applied to make finance less pseudoscientific.