Plectics - The study of simplicity and complexity (1996) | Hacker News Reader

Plectics - The study of simplicity and complexity (1996)

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26 pointshhs7 comments

Fancy name. Last I've seen this it was called cybernetics and is still alive. (Also complexity science. It is sort of a branch of both cybernetics and information science. No, not just CS.)

Opening quote:

> J. Doyne Farmer: The first thing that makes me respect Murray is that unlike all his contemporaries, including Feynman, Weinberg, Hawking, and all the other particle physicists, he saw that complexity is the next big problem.

Hawking in 2000[0]:

> I think the next century will be the century of complexity.

So I guess he came around to Gell-man's thinking eventually!

What I don't understand is why we aren't engaging with complexity more openly and directly. The limitations and challenges imposed by constantly increasing complexity loom before us and are manifested in the global economic, ecological, and political problems we're seeing.

My opinion is that these limitations and the challenges of continuing to progress despite increasing complexity are what make up this Great Filter that explains the Fermi Paradox.

You can't become multi-planetary (let alone multi-solar) without an amazing set of complex technical systems that requires a stable organizational system to develop and produce over a long period of time. So first you need to solve the problem of how to maintain stability in an enormously complex organizational system long enough for these kinds of technical systems to emerge.

Complexity is an ever-growing albatross around our collective necks and I feel very alone when I'm arguing against any number of far-flung beliefs, like in trans-humanism and AGI fears/hopes, and can't seem to explain how complexity is the regulating phenomenon that makes what these people think is a perpetual exponential curve of progress into the same sigmoid curve that we observe whenever any other organism finds a way to exploit their environment.

[0] https://blogs.scientificamerican.com/the-curious-wavefunctio...

I generally agree, and it's something I asked myself very often too. It's the kind of problem that makes you wonder: "why don't I hear more people talking about it?". Well, I would expect to hear it more, at least from clever people tackling complicated problems. At the same time, I also noticed that the more complex problems you tackle, the more problems that could use solutions you start to see. So maybe you get into that loop of "there's so many things to do!", that even if you think about complexity from time to time, you are just too busy dealing with that complexity already, or learning/studying/getting into something new, etc.

I don't know, I think it's very interesting, I'd like to read more opinions on this.

Good points, I also agree with your note, "What I don't understand is why we aren't engaging with complexity more openly and directly. The limitations and challenges imposed by constantly increasing complexity loom before us and are manifested in the global economic, ecological, and political problems we're seeing."

What would push complexity research forward? In my view, a greater concentration of empirical works would give this field more attention.

There's a useful YouTube channel by the Santa Fe Institute that broadcasts research in this field. Last month, there was a good presentation by Srividya Iyer-Biswas.

Based on the Santa Fe Institute's channel: "Iyer-Biswas and her team have reported predictive scaling laws governing the stochastic growth and division of cells, and have developed a theory that reveals the emergence of a scalable, cellular unit of time. Her current work involves extending these results to thermodynamics of organismal computation, time-dependent phenomena involving cellular decision-making, and laws that dictate complex biological and social phenomena."

If interested, the video is here: https://www.youtube.com/watch?v=wV1mWE8Zyi0.

The Santa Fe Institute also offers free online courses on complexity-related topics (e.g. fractals, chaos, nonlinear systems, etc) at https://www.complexityexplorer.org/

Definitely, that's a useful place to get a grasp of complexity topics, thanks for sharing.

AD: Its one of those areas I don't see come up AT ALL on HN, complexity theory [0] imho is a superset to all software engineering practises, because people are involved and not just because the things we are trying to solve are 'complex'.

A great place to start is Dave Snowden's Cynefin sense-making framework [1][2]. Study it and embed it into your core thinking, it can underpin how you approach almost every problem you come across in life. I was fortunate enough to attend a masterclass with Dave Snowden and Simon Wardley (Wardley maps, another thing worth understanding and practising related to strategy, he's published the whole thing for free on Medium [3]). What was fascinating and part of the result of the 2 day class is that Simon Wardley had been using a Cynefin like model in his head whilst making decisions and when he came up with his mapping method, additionally they had both been inspired by Max Boisot [4].

[0] https://en.wikipedia.org/wiki/Complexity_theory_and_organiza... [1] https://en.wikipedia.org/wiki/Cynefin_framework [2] http://cognitive-edge.com/videos/cynefin-framework-introduct... [3] https://medium.com/wardleymaps/on-being-lost-2ef5f05eb1ec [4] https://en.wikipedia.org/wiki/I-Space_(conceptual_framework)

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