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We must seek a widely-applicable science of systems

hiranmay.xyz

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Re: We must seek a widely-applicable science of systems

#41

Post by bbor »

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

Re: We must seek a widely-applicable science of systems

#42

Post by bbor »

endiangroup wrote: post #16

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 Computati…

What do you suggest we do instead of modeling complex systems…? Isn’t that kinda an important part of aerospace, psychology, and meteorology, just to name three random things? Likely misinterpreting; I doubt anyone is anti-modeling in general!

Re: We must seek a widely-applicable science of systems

#43

Post by bbor »

datadrivenangel wrote: post #20
endiangroup wrote: post #16

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 Computati…

Exactly. All human systems are sociotechnical, and people within systems respond differently when they know that they're being monitored, and even more differently when they know that the monitors know that they know they're being monitored. Exact models are somewhere between impossible and implausibly expensive for a non-trivial system. Approximate or die.

What’s not exact about a human brain…? Complex, sure. But I don’t see the difference in kind you allude to

Re: We must seek a widely-applicable science of systems

#44

Post by feoren »

vitalnodo wrote: post #39

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 in…

This is the problem I have with any study of "systems". It all just feels like overly ornate verbiage for "hey, this thing kinda looks like this other thing if you squint". It's very difficult to distinguish that imgur image from complete Time-Cube-level quackery. "Volume (more than 3 points) deep cause-and-effect relationships trivalent linguistics (he gives the book to his brother)" ... really? Is this really helping humanity understand anything?

Re: We must seek a widely-applicable science of systems

#45

Post by omnicognate »

AndrewKemendo wrote: post #31
endiangroup wrote: post #16

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 Computati…

The field of cybernetics covers 100% of this context The fact that nobody considers cybernetics an actual functional study is an unmitigated tragedy - based on politics - that needs to be fixed immediately Wiener, etc. laid the whole thing out, gave a very compelling and clear way to approach questions and complexity, and we are just as a field completely ignoring it to our own detriment with this idea that somebody…

Any recommendations for learning it?

Re: We must seek a widely-applicable science of systems

#46

Post by burnished »

bbor wrote: post #43
datadrivenangel wrote: post #20

Earlier quoted context omitted.

Exactly. All human systems are sociotechnical, and people within systems respond differently when they know that they're being monitored, and even more differently when they know that the monitors know that they know they're being monitored. Exact models are somewhere between impossible and implausibly expensive for a non-trivial system. Approximate or die.

What’s not exact about a human brain…? Complex, sure. But I don’t see the difference in kind you allude to

As it turns out, pretty much everything. Individual neurons are imprecise and adaptive and they form networks that show chaotic behavior.

Basically I'd turn the question around - what makes you think brains are exact?

Re: We must seek a widely-applicable science of systems

#47

Post by navaati »

bbor wrote: post #43
datadrivenangel wrote: post #20

Earlier quoted context omitted.

Exactly. All human systems are sociotechnical, and people within systems respond differently when they know that they're being monitored, and even more differently when they know that the monitors know that they know they're being monitored. Exact models are somewhere between impossible and implausibly expensive for a non-trivial system. Approximate or die.

What’s not exact about a human brain…? Complex, sure. But I don’t see the difference in kind you allude to

It does not help you having a perfect and exact rule from initial conditions to future prediction... if you cannot have a complete and exact description of your initial conditions.

We might never be able to get this exact description of the internal state of a brain, this is what makes perfect prediction impossible.

Re: We must seek a widely-applicable science of systems

#48

Post by skndr »

omnicognate wrote: post #45
AndrewKemendo wrote: post #31

Earlier quoted context omitted.

The field of cybernetics covers 100% of this context The fact that nobody considers cybernetics an actual functional study is an unmitigated tragedy - based on politics - that needs to be fixed immediately Wiener, etc. laid the whole thing out, gave a very compelling and clear way to approach questions and complexity, and we are just as a field completely ignoring it to our own detriment with this idea that somebody…

Any recommendations for learning it?

I recommend:

- Designing Freedom by Stafford Beer

- Brain of the Firm by Stafford Beer

- Thinking in Systems by Donella Meadows

Re: We must seek a widely-applicable science of systems

#49

Post by marcusverus »

hdarshane wrote: post #6
dav wrote: post #4

Somewhat related, I feel like the book Thinking in Systems should be taught in high school https://www.goodreads.com/book/show/3828902

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?

I'm inclined to say it's mostly inertia.

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.

Re: We must seek a widely-applicable science of systems

#50

Post by openrisk »

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 :-)

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