Griffith University Yunus CentreAug 17·5 min read·ListenLayering portfolios in context. Developed by The Yunus Centre Griffith University & Hatched for Design Foundations for Systems CapitalDesign Foundations For Systems CapitalDesigning an investment approach that fosters systems innovation and transformation
Design Foundations For Systems Capital | by Griffith University Yunus Centre | Y Impact | Aug, 2022 | Medium
h/t Mikael Seppala
Disentangling the evolutionary drivers of social complexity: A comprehensive test of hypotheses | Science Advances
h/t Michael Garfield
PETER TURCHIN HTTPS://ORCID.ORG/0000-0002-1292-8100HARVEY WHITEHOUSE HTTPS://ORCID.ORG/0000-0001-6935-6724 SERGEY GAVRILETSDANIEL HOYER HTTPS://ORCID.ORG/0000-0003-2675-257XPIETER FRANÇOISJAMES S. BENNETT HTTPS://ORCID.ORG/0000-0003-3051-1672KEVIN C. FEENEYPETER PEREGRINE HTTPS://ORCID.ORG/0000-0001-9185-3348GARY FEINMAN HTTPS://ORCID.ORG/0000-0002-4787-2733[…]MAJID BENAM +8 authors Authors Info & Affiliations
SCIENCE ADVANCES
24 Jun 2022
Vol 8, Issue 25
During the Holocene, the scale and complexity of human societies increased markedly. Generations of scholars have proposed different theories explaining this expansion, which range from broadly functionalist explanations, focusing on the provision of public goods, to conflict theories, emphasizing the role of class struggle or warfare. To quantitatively test these theories, we develop a general dynamical model based on the theoretical framework of cultural macroevolution. Using this model and Seshat: Global History Databank, we test 17 potential predictor variables proxying mechanisms suggested by major theories of sociopolitical complexity (and >100,000 combinations of these predictors). The best-supported model indicates a strong causal role played by a combination of increasing agricultural productivity and invention/adoption of military technologies (most notably, iron weapons and cavalry in the first millennium BCE).
Disentangling the evolutionary drivers of social complexity: A comprehensive test of hypotheses
Disentangling the evolutionary drivers of social complexity: A comprehensive test of hypotheses | Science Advances
Bobby Azarian has apparently been on the Joe Rogan thing. This was advertised on linkedin (https://www.linkedin.com/posts/arasharabi_using-neuroscience-cybernetics-to-transform-activity-6962555285450211329-U3Wk?utm_source=linkedin_share&utm_medium=member_desktop_web) by Arash Arabi where I said:
“Congrats on a really professional and interesting podcast / video interview…. I must admit I thought it seems like he knows his stuff and was giving a wide overview, but because it was *such* a wide overview, without real reference points to which theory (and which versions) he was referencing, I lost track bit and was unable to see what the ‘new perspective’ was that he was bringing. Perhaps I’m not at my best this evening, or perhaps I’m not the target audience 🙂
Anyway, I’ve subscribed and will share!”“PS I have a real prejudice against neuroscience (sorry!) so I was quite pleased to see it didn’t seem to really feature – but I don’t think cybernetics (which I am prejudiced in favour of!) really featured either?”
I would value perspectives on this!
Using neuroscience & cybernetics to transform social organisations | Bobby Azarian & Arash Arabi – YouTube
It’s true — but it’s not the whole story.
And because it’s a one-sided argument trying to rebalance a polarised, competitive world — arguments for ‘holism’ can undermine themselves by missing out the reality of people’s lives.
Here are eight things to think about re complexity | systemsthinking | cybernetics. They apply for management, innovation, society, ecology.
1 denying that we are part of a whole
It’s true: we are all connected. You can’t throw anything ‘away’ because there’s no ‘away’.
This insight can change lives — deeply, fundamentally. It can change organisations, and society — usually for the better.
But despite our best wishes and intentions, it somehow doesn’t change the world! Why?
2 believing we have seen the whole when…
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Rude! 😉
I prefer to comment on a blog, on the blog itself. It helps to convert them from monologue to dialogue: which all bloggers appreciate. On this occasion, however, I have got too much to say and it would distract from the excellent blog on Lean, published by Joy Furnival.
A few weeks ago, while Joy was musing over Lean ‘being blamed for various supply chain failings’, we exchanged some thoughts on twitter, just to get the creative juices flowing. It looks like, given the tweets and the subsequent blog that we agree on many things, albeit from different perspectives, but I feel obliged to expand on a couple of Joy’s points, opinions, insinuations.
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Last month I reread (and blogged) Churchman’s ‘The Systems Approach’ (1968) and was surprised to see that between the lines it contained practically the whole of the dialectical systems approach (the systems approach) as it finally took shape in 1971 (The design of inquiring systems) and 1979 (Enemies of the systems approach). In ‘The Systems Approach’ Churchman describes in fact how the dialectical systems approach emerged from the scientific systems approach (the “systems approach”) and operations research, something he had been working on very successfully from 1941 onward and the 1950s in particular, culminating in his ‘Introduction to Operations Research’ (IOR, Wiley, 1957; co-written by Russ Ackoff and Leonard Arnoff, one of the big guys behind Ernst & Young). Interestingly and speaking in a general sense, many of the ideas of ‘The Systems Approach’ of 1968 can be traced back in…
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Modern society [1] Niklas Luhmann (1927-1998) was a German sociologist who developed a general systems theory of modern society. The American social systems theorist Talcott Parsons (1902-1979) was a major influence – for the idea of social systems -, but so were the Chileans Humberto Maturana (1928-2021) and his student Francisco Varela (1946-2001) – for the idea of autopoiesis. Steffen Roth (1976) is a very active Luhmann scholar. According to Luhmann modern society evolved from the 16th to 18th century by differentiating largely independent function systems such as law, politics, science, economy, religion, and media. The function systems were not so much human designs as globally emerging patterns of social differentiation in a historically evolving environment, which to a large extent was shaped by those same emerging function systems. ‘Social systems theory does not describe reality as it “essentially” is, but as what it has actually become – and it…
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The dynamics of transitions in socio-technical systems: A multi-level analysis of the transition pathway from horse-drawn carriages to automobiles (1860–1930)Dr. Ir. F. W. Geels
The dynamics of transitions in socio-technical systems: A multi-level analysis of the transition pathway from horse-drawn carriages to automobiles (1860–1930): Technology Analysis & Strategic Management: Vol 17, No 4
Is reduction always a good scientific strategy? The existence of the special sciences above physics suggests not. Previous research has shown that dimensionality reduction (macroscales) can increase the dependency between elements of a system (a phenomenon called ‘causal emergence’). Here, we provide an umbrella mathematical framework for emergence based on information conversion. We show evidence that coarse-graining can convert information from one ‘type’ to another. We demonstrate this using the well-understood mutual information measure applied to Boolean networks. Using partial information decomposition, the mutual information can be decomposed into redundant, unique and synergistic information atoms. Then by introducing a novel measure of the synergy bias of a given decomposition, we are able to show that the synergy component of a Boolean network’s mutual information can increase at macroscales. This can occur even when there is no difference in the total mutual information between a macroscale and its underlying microscale, proving information conversion. We relate this broad framework to previous work, compare it to other theories, and argue it complexifies any notion of universal reduction in the sciences, since such reduction would likely lead to a loss of synergistic information in scientific models.
This article is part of the theme issue ‘Emergent phenomena in complex physical and socio-technical systems: from cells to societies’.
Emergence as the conversion of information: a unifying theoryThomas F. Varley and Erik HoelPublished:23 May 2022
Emergence as the conversion of information: a unifying theory | Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
34C3- Reflections on the Hacker Ethos // Chaos Engineering
January 2018m Eirini Malliaraki
Aug 10
“Scepticism does not mean the successive doubting, item by item, of all opinions or of all the pathways that accede to knowledge. It is holding the subjective position that one can know nothing…. Scepticism is something that we no longer know. Scepticism is an ethic. Scepticism is a mode of sustaining man in life, which implies a position so difficult, so heroic, that we can no longer even imagine it — the way of desire.” -Lacan, 1977I spent the last 4 days celebrating hacker culture at the Chaos Communication Congress in Leipzig. The 34C3 is an annual conference organised by the hacking collective Chaos Computer Club. It features a variety of lectures and workshops on technical and political issues related to security, privacy, open source technologies and freedom. The community consists of all people of the web who share the common vision for an open and free technological society: trolls, programmers, activists, artists, philosophers, engineers and every virtual creature in-between. In this post, I’d like to talk about my experience and my interpretation of the hacker ethos.
34C3- Reflections on the Hacker Ethos // Chaos Engineering
(With cybernetics, complexity, and chaos)
Why is top-down causation so problematic for many? Is it a consequence of their lifelong bias towards substance metaphysics?
(2) Carlos E. Perez on Twitter: “Why is top-down causation so problematic for many? Is it a consequence of their lifelong bias towards substance metaphysics?” / Twitter
See also
Here is a list of complexity science books in a popular science style from when the hype was the biggest—from 1988 and a decade further*—and some very brief comments. Several of them are available at archive.org, as linked below. I’m pretty sure I forgot several. If so, I’ll add them later.
* I’m no longer the film buff I used to be, but this reminds me of the golden age of Hong Kong police action films which most fans agree, with surprisingly little discussion, was from 1984 to 1993. (And, yes, John Woo’sHard Boiledis the crown jewel of the genre.)
HR Pagels, 1988.The Dreams of Reason: The Computer and the Rise of the Sciences of Complexity. Simon and Schuster, New York.
We’ll kick off with maybe the most remarkable of all these books (and the most interesting…
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Amos Golan and John Harte
PNAS 119 (33) e2119089119
Modeling and inference are central to most areas of science and especially to evolving and complex systems. Critically, the information we have is often uncertain and insufficient, resulting in an underdetermined inference problem; multiple inferences, models, and theories are consistent with available information. Information theory (in particular, the maximum information entropy formalism) provides a way to deal with such complexity. It has been applied to numerous problems, within and across many disciplines, over the last few decades. In this perspective, we review the historical development of this procedure, provide an overview of the many applications of maximum entropy and its extensions to complex systems, and discuss in more detail some recent advances in constructing comprehensive theory based on this inference procedure. We also discuss efforts at the frontier of information-theoretic inference: application to complex dynamic systems with time-varying constraints, such as…
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Systems Community of Inquiry 
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