The Overview - June 05, 2020
The Overview is a weekly roundup of eclectic content in-between essay newsletters & "Conversations" podcast episodes to scratch your brain's curiosity itch.
|Nicholas McCay||Jun 5, 2020|
Hello Eclectic Spacewalkers,
I wish that you and your family are safe & healthy wherever you are in the world. :)
Here are some eclectic links for the week of June 5th, 2020. This week's theme is "Complexity"
Check out last week’s roundup HERE.
Lastly, be on the lookout for essay #11: Updated Operating Manual for Spaceship Earth on Monday (June 8th). - Delayed due to attending #BlackLivesMatter protests.
Enjoy, share, and subscribe!
Table of Contents:
Articles via Phys.org, The New Yorker, Ethical Markets, Naked Capitalism, Joe Norman, The Side View
Book - Thinking in Systems: A Primer, Chaos: Making a New Science by James Gleick, Complexity Reading List, 52 best complexity books of all time via Book Authority
Course - Complexity Theory via Systems Innovation
Discussion - Fritjof Capra’s Systems View of Life: A Conversation between Fritjof Capra & Daniel Wahl
Documentaries - Butterfly - The Secret Life of Chaos, The Human Body: The ultimate frontier of complexity
Lecture - P vs NP problem: What Computers Can't Do - with Kevin Buzzard
Papers - Statistical physics of self-replication, Emergent Phenomena and Complexity, General complexity: A philosophical and critical perspective, Complex Systems, Evolution and the Management of Manufacturing Change, We can’t get here from there: Sustainability from complexity vs. conventional perspectives
Podcast - BBC In Our Time, Santa Fe Institute, The Human Current, and The Art of Complexity
Short Film - Fritjof Capra speaks to The Heart of the Matter: A systems approach for achieving the UN Sustainable Development Goals., Brilliant Accidents via Exurb1a
TED Talks - The complexity of emergent systems: Joe Simkins at TEDxColumbus
Twittersphere - @normomics, @cognitivepolicy, @ESpacewalk
Website - Complexity Explorer via Santa Fe Institute, Systems Innovation, The Complexity Zoo, Chaos & Complexity Theory, Cognitive Edge
The four horsemen of the COVID-19 pandemic — via Phys.org
“A new article by Kang Hao Cheong and Michael C. Jones published in BioEssays describes the convergence of four broad, but easily identifiable systemic, pathologically networked conditions, or "four Horsemen," that are hurtling civilization towards potential self-destruction in which a pandemic is only one of many possible triggers.
The "four Horsemen" of overpopulation, globalization, hyperconnectivity and increasingly limited and centralized supply chains are the broad parameters underlying the probability space of catastrophe.”
The Pandemic Isn’t a Black Swan but a Portent of a More Fragile Global System — via The New Yorker
“We should discourage the concentration of power in big corporations, “including a severe restriction of lobbying,” Taleb told me. “When one percent of the people have fifty percent of the income, that is a fat tail.” Companies shouldn’t be able to make money from monopoly power, “from rent-seeking”—using that power not to build something but to extract an ever-larger part of the surplus. There should be an expansion of the powers of state and even county governments, where there is “bottom-up” control and accountability. This could incubate new businesses and foster new education methods that emphasize “action learning and apprenticeship” over purely academic certification. He thinks that “we should have a national Entrepreneurship Day.”
But Taleb doesn’t believe that the government should abandon citizens buffeted by events they can’t possibly anticipate or control. (He dedicated his book “Skin in the Game,” published in 2018, to Ron Paul and Ralph Nader.) “The state,” he told me, “should not smooth out your life, like a Lebanese mother, but should be there for intervention in negative times, like a rich Lebanese uncle.” Right now, for example, the government should, indeed, be sending out checks to unemployed and gig workers. (“You don’t bail out companies, you bail out individuals.”) He would also consider a guaranteed basic income, much as Andrew Yang, whom he admires, has advocated. Crucially, the government should be an insurer of health care, though Taleb prefers not a centrally run Medicare-for-all system but one such as Canada’s, which is controlled by the provinces. And, like responsible supply-chain managers, the federal government should create buffers against public-health disasters: “If it can spend trillions stockpiling nuclear weapons, it ought to spend tens of billions stockpiling ventilators and testing kits.”
At the same time, Taleb adamantly opposes the state taking on staggering debt. He thinks, rather, that the rich should be taxed as disproportionately as necessary, “though as locally as possible.” The key is “to build on the good days,” when the economy is growing, and reduce the debt, which he calls “intergenerational dispossession.” The government should then encourage an eclectic array of management norms: drawing up political borders, even down to the level of towns, which can, in an epidemiological emergency, be closed; having banks and corporations hold larger cash reserves, so that they can be more independent of market volatility; and making sure that manufacturing, transportation, information, and health-care systems have redundant storage and processing components. (“That’s why nature gave us two kidneys.”) Taleb is especially keen to inhibit “moral hazard,” such as that of bankers who get rich by betting, and losing, other people’s money. “In the Hammurabi Code, if a house falls in and kills you, the architect is put to death,” he told me. Correspondingly, any company or bank that gets a bailout should expect its executives to be fired, and its shareholders diluted. “If the state helps you, then taxpayers own you.”
Some of Taleb’s principles seem little more than thought experiments, or fit uneasily with others. How does one tax more locally, or close a town border? If taxpayers own corporate equities, does this mean that companies might be nationalized, broken up, or severely regulated? But asking Taleb to describe antifragility to its end is a little like asking Thomas Hobbes to nail down sovereignty. The more important challenge is to grasp the peril for which political solutions must be designed or improvised; society cannot endure with complacent conceptions of how things work. “It would seem most efficient to drive home at two hundred miles an hour,” he put it to me.“But odds are you’d never get there.””
The COVID-19 Pandemic: A Systemic Analysis — via Ethical Markets
“Ethical Markets is happy to post this latest update “The COVID-19 Pandemic—A Systemic Analysis” from our esteemed Advisory Board member, best-selling author, physicist Fritjof Capra. This complements the earlier article we co-authored “Pandemics: Lessons Looking Back from 2050“, published in March and discussed on our April 2nd webinar. Since then there is continuous new information and so we have both written updates expanding from our complimentary perspectives!
Our emerging view sees the possibility that this “teachable moment“ opens up new ways of building a more sustainable future for all, as we see various versions of “Green New Deals” now a political and grassroots agendas in the USA, EU, and some 130 countries! Let’s keep networking and pushing for this positive future, envisioned in the practical, achievable UN sustainable Development Goals (SDGs) by 2030!
~Hazel Henderson, Editor”
Taleb: The Only Man Who Has A Clue — via Naked Capitalism
“It says something not good at all about the state of medicine, public health, and the leadership of Western societies generally that it’s Taleb who has been speaking relentlessly, and largely alone, about the importance of the precautionary principle. It may be that Taleb, in his usual iconoclastic fashion, brought it up in the context of GMOs, where supposedly only cranks worry about safety. Perhaps my sample is skewed, but the one person I know who is ex the NIH (later went to Big Pharma and then to FDA/intellectual property law) thought that GMOs were an appalling abuse: a mass experiment conducted with no controls and no consent. And even though she wasn’t at all a health nut (she relished the occasional burger and fries and would eat junk food from the snack machine if she was stuck late at the office), she avoided GMOs until she gave up, saying it was too hard.
There are many important takeaways from this discussion, but one stood out for me: Taleb and his fellow risk analysts argue that contact tracing is of little use once a disease has hit the pandemic stage.”
This Professor Says We've Been Looking At The Coronavirus Data Wrong — via Forbes
Yaneer says, “Why do we need the science of complex systems? If there are dependencies in the systems, then statistics don’t work. Standard calculus can’t describe things properly when there are abrupt large scale changes that involve changes in what many individuals are doing.”
No matter what models you use, you are selecting a group of variables that will give you the best picture of the answers that you seek. Depending on the data, with the right variables, you will gain the answers you are looking for. But, with the wrong variables, you can be drastically misled.
Yaneer says, “Often, it’s not the math that is wrong. It’s the variables that are wrong. You need to figure out what the right variables are. When people write down models, there’s a perspective that you have to include all the details. That’s not the case. It’s not possible to include everything. So you may miss something important. At the same time, most of the details are not important.”
Complex Systems Science: An Informal Overview — Part I: Reductionism and Emergence — via Joe Norman
“This is the first in a series of short blog posts where I will discuss some of the major themes in complex systems science in an informal, and hopefully accessible, way. The perspective is my own, and might differ from others’ takes on these concepts.
From these concepts and themes I will distill implications for real-world decision-making, and rather than applying specific results to a specific problem, I will emphasize the big picture and ‘lessons learned’. So, let’s get started with a small dose of philosophy.
To get a sense of the essence of complex systems science, it is important to understand the philosophy of reductionism. Reductionism asserts that to understand something, it is sufficient to (1) break it down into its ‘natural’ parts, (2) study the properties of those parts.
Said differently, a reductionistic philosophy assumes that any property of a whole is inherited directly from a corresponding property of a part of the system.
Complex systems science recognizes the insufficiency of reductionism to understand and describe our world — especially the most interesting and relevant phenomena: living, social, civilizational, systems.
To be clear, this is not a claim the reductionist methodologies are never appropriate, just that by themselves they are insufficient.
Reductionism has become so ingrained in our way of thinking it is sometimes difficult to imagine what the alternative could be. Recall that reductionism assumes that if a system, call it S, has a property, call it P, then P must be present in at least one of the parts that compose S.
Clearly, the alternative is that property P of S is not present in any part of S. How can this be?
The answer is that P emerges from interactions of component parts of S. Let’s make this concrete with an example.
We all know that the brain is involved in recognizing patterns. For example, we see a pattern of light and know it is a face, or we might even recognize the pattern as our Grandmother. So it is safe to say ‘pattern-recognition’ is a property of the system ‘brain’.
The brain is composed of parts called neurons. In a simplified description, a neuron is either ON or OFF. When it is ON, it sends signals to other neurons it is connected to that it is ON. Each neuron, at each moment in time, adds up the signals being sent to it, and makes a simple decision whether to be ON or OFF. That is essentially it. No pattern-recognition property to be found in any neuron.
However, when these neurons are connected into networks, they are able to recognize complex patterns, such as human faces. How those networks come to be and how they function to do cognitive work can be saved for another time, just trust me here that it works.
The important point here is that the property, pattern-recognition, emerges at the scale of the system, a network of neurons (brain), without any part of the system having such a property.
Complex Systems Science: An Informal Overview — Part II: Organization and Scale — via Joe Norman
Complex Systems Science and the Special Sciences
We are familiar with science being broken down into different categories depending on what is being studied: particle physics (e.g. electrons), chemistry (molecules), biology (organisms), psychology (minds), sociology (groups of humans), etc. Call these the special sciences as their role is to look into a certain kind of stuff.
Complex systems science is not defined by what the stuff under study is, but rather how one asks and attempts to answer questions about whatever stuff is of interest. Recall that in complex systems, the properties we are interested in might emerge from interactions among components, i.e. emergent properties. For this reason, in complex systems science we pay special attention to the interactions and relationships among the parts, and how they give rise to (emergent) patterns of behavior.
We can do this in physical systems, biological systems, social systems, or any other system of interest. The answers we get will often look remarkably different than those from the special sciences.
Organization and Interdependence
When we attend to the interactions and relationships in a system, the organization of the stuff becomes more central to our understanding than the stuff itself. To illustrate this point, imagine a mad scientist takes each cell of your body one by one and relocates it to a random location — would you feel much like yourself? I think not. When the organization is disrupted, so are the interactions, and the nature of the system changes.
This also means when you change one part of the system, you may affect a larger portion of, or even the whole, system. This is because the behavior of the parts are interdependent. What part A is doing affects what part B & C are doing (and perhaps vice verse) — what my heart is doing affects what my lungs and muscles are doing. Interdependent behavior presents all kinds of challenges to standard statistical approaches which assume the independence of parts of a system.
Whether or not the change in one part of a system has affects on other parts of the system depend on its organization. If you had to choose between losing a kidney or a heart, which would you choose? Would a tree do better off losing ten-thousand leaves or one trunk?
These are hints to be cautious of centralization, and to use redundancy for robustness when possible. When we build systems we should ask ourselves, “what would happen if X failed?” — even if we are pretty sure X won’t fail.
More is Different
‘More is different’ is another way of saying ‘emergence happens’. It is no easy task to predict what the emergent effects will be when we scale a system (i.e. increase its size/number of components), especially when operating under reductionistic assumptions (emergent effects will always surprise the reductionist).
When engineering systems, emergent effects are often detrimental, or even catastrophic, to the integrity of the system, and therefore the purpose it was intended to fulfill. This is because, at the smaller scale, what appear as irrelevant side-effects (which may not have been noticed or attended to at all) are able to be absorbed or dissipated into the system’s environment in some way or another. When we grow the system, these ‘side-effects’ can coalesce and become relevant to the behavior of the system.
This is why we don’t see land animals much bigger than elephants throughout Earth’s history: the mechanical forces that are mere side-effects for smaller critters become causes of failure. Darwin puts a harsh limit on the scale of a design motif.
There are countless engineering failures that are of enormous cost to society (e.g. F-35, USS Zumwalt, the global financial system). Overgrown elephants.
The holy grail of systems engineering is to leverage emergence rather than fighting against it. Nature manages to do this via evolutionary tinkering. Perhaps we can take a cue from her.”
What is Warm Data?
Warm Data is that other kind of information: the emulsifier at the unspoken levels of why anyone does what they do. To make sense of our world we need all of our senses in relation to each other. Warm Data is the messy stuff, the multi-contexted, non-measureable relations between those senses. It is the movement within a complex living system. Warm Data is information that is alive. Warm Data itches when it is confined. Warm Data is the kind of information that let’s you know when to tell someone you love them. Warm Data gives credence to the notion that a deeply human response to complexity is possible. We all have it. Warm Data is why setting up multiple committees to solve the world’s problems of ecological and economic disaster will never work. The issues can never be separated. Warm Data is not located in one spot, or definable from one context—it changes, it is paradoxical, it matters who is observing.
Warm Data is the relational information; it’s not about the family members, but the relationship between them; it’s not about the organisms in a forest, but the relations between them; it’s not about the institutions of a society, but the relations between them.
There are different ways of generating Warm Data. One is research on complex issues. This form of research generates inquiry that does not get caught in either time-frozen or decontextualized research projects. Another form of participation is the Warm Data Lab. But, since the Warm Data Lab is an in-person process, it is currently on hold for the time it takes before travel and group gatherings are allowed again. In the meantime, a community-based project, called People Need People (PNP) has begun. It was originally designated for helping communities begin to perceive and articulate the possible projects that would form responses to the complexity of the issues they are facing, as opposed to silo-ed solutions. In a hurry, this process had to go online. I was against it. I fought hard. I was worried that the tech would flatten the richness of the in-person labs. What would happen to the shared experience of the room, to the subtle cues of a group laughing loudly, to the nuance of body language? But I eventually found a design for the process, and with a few different teams around the world, we prototyped it in a rush. That process is now known as PNP Online, and it’s running in about 40 different places around the world now, aided by around 100 certified PNP hosts.”
(Read our Systems Thinking essay based on the above here: https://eclecticspacewalk.substack.com/p/eclectic-spacewalk-2-systems-thinking)
So, the subject of my course, which is called officially, The Systems View of Life, but for PR purposes, Capra Course. Because it’s easy to remember, and it has a website, capracourse.net. So, it is based on the textbook that I wrote with Luigi, the Four Dimensions of The Systems View of Life. Integrating the biological, the cognitive, the social and the ecological. It consists of 12 prerecorded lectures of about 40 minutes and they were recorded for some reason in Brazil. In the home of an architect, a beautiful living room with a very small group of participants. I can tell you, I don’t know whether you realize this watching the lectures. That this is really modeled after Schumacher College, because when you see people sitting on the floor and on couches in this intimate environment discussing things. That’s what I’ve done with people at Schumacher College for 20 years. So, I modeled my lectures after that and in addition to the lectures, there’s a discussion forum. `
An online discussion forum, where people post comments and questions, and I participate in that during the whole course. So for 12 weeks, one lecture a week, I’m there every day for about half an hour to an hour answering questions. That has been a real experience for me because, although I don’t have the face to face contact with people that I have in a classroom. The conversations and the discussions are much more substantial because in a classroom, when you teach in a classroom and somebody asks you a question. You have to say something, you have to answer whether you know an answer or not, you have to say something. Online, that’s not true, I can go away and do some research, I can look at books, I can browse the internet, I can think about it. Usually, what I do in the morning when I brush my teeth during the course and shave. I check the questions first, when I get up and then I think about it and mild them over. Then, I go and discuss things with my students…
So, as you mentioned, the course has now run for four years. We have 1300 more or less alumni around the world, I think in 70 countries now on all continents and even in the single course. The next course is starting on the 26th of February and I have these postcards. We have over a 100 registrations now for the 26th of February, from about 30 countries around the world, from all continents. So like a Schumacher College, it’s this multicultural, global community. We have so many alumni now, that we have alumni meetings on Zoom, like you and I have right now. But also, face to face because whenever I travel somewhere I meet alumni. Whether they go to Italy or to Austria, or to London or to Sweden, I have alumni meetings and I don’t need to be there. They have alumni meetings in Rio de Janeiro, and in Buenos Aires, and various places around the world. So, I’m really realizing my dream here to grow a global community, a global network of systemic thinkers and activists. It’s very fulfilling to me.”
“Self-replication is a capacity common to every species of living thing, and simple physical intuition dictates that such a process must invariably be fueled by the production of entropy. Here, we un- dertake to make this intuition rigorous and quantitative by deriving a lower bound for the amount of heat that is produced during a process of self-replication in a system coupled to a thermal bath. We find that the minimum value for the physically allowed rate of heat production is determined by the growth rate, internal entropy, and durability of the replicator, and we discuss the implications of this finding for bacterial cell division, as well as for the pre-biotic emergence of self-replicating nucleic acids.”
“I seek to define rigorously the concept of an emergent phenomenon in a complex system, together with its im- plications for explanation, understanding and prediction in such systems. I argue that in a certain fundamental sense, emergent systems are those in which even perfect knowledge and understanding may give us no predictive information. In them the optimal means of prediction is simulation. I investigate the consequences of this for cer- tain decidability and complexity issues, and then explain why these limitations do not preclude all means of doing interesting science in such systems. I touch upon some recent incorporation of this work into the investigation of self-organised criticalities.”
General complexity: A philosophical and critical perspective Minka Woermann, Oliver Human, Rika Preiser
“In this paper we argue that a rigorous understanding of the nature and implications of complexity reveals that the underlying assumptions that inform our understanding of complex phenomena are deeply related to general philosophical issues. We draw on a very specific philosophical interpretation of complexity, as informed by the work of Paul Cilliers and Edgar Morin. This interpretation of complexity, we argue, resonates with specific themes in post-structural philosophy in general, and deconstruction in particular. We argue that post-structural terms such as différance carry critical insights into furthering our understanding of complexity. The defining feature that distinguishes the account of complexity offered here to other contemporary theories of complexity is the notion of critique. The critical imperative that can be located in a philosophical interpretation of complexity exposes the limitations of totalising theories and subsequently calls for examining the normativity inherent in the knowledge claims that we make. The conjunction of complexity and post-structuralism inscribes a critical-emancipatory impetus into the complexity approach that is missing from other theories of complexity. We therefore argue for the importance of critical complexity against reductionist or restricted understandings of complexity.”
Complex Systems, Evolution and the Management of Manufacturing Change - Dr Christen Rose-Anderssen, Dr James Baldwin, Prof Keith Ridgway
“The aim of this paper is to provide a natural framework for the management of manufacturing change. The framework is designed, firstly, by describing the characteristics of dissipative structures. This is expanded upon by presenting the essentials of complex systems in way of evolution. Darwinian evolution and change is then discussed from a perspective of complex systems. The classification instruments of change are explained in terms of the complex system and evolutionary perspectives. Then the application of the classification instruments are demonstrated through a case of discrete manufacturing systems.”
We can’t get here from there: Sustainability from complexity vs. conventional perspectives - Dr. Terry Porter, Randall Reischer
“Sustainability problems are today becoming more prevalent, more systemic and more serious than ever before. And they are expanding, from operational inconveniences that could largely be addressed through line-level fixes, to boardroom enigmas and political groundswells that defy traditional boundaries. This paper argues that these shifts in the nature of sustainability problems are highly significant for researchers as well. They indicate that the ontology of sustainability issues is also shifting: it is growing increasingly complex. We can no longer speak meaningfully about social, environmental and economic sustainability issues as isolated, independent incidents. With growing acceptance that “everything is connected to everything else”,1 we recognize that we must progress beyond sole use of conventional reductionist epistemologies. Growing complexity is not a descriptive term, but rather an ontological watershed between classical Newtonian assumptions of linearity, stability, and reductionistic inquiry on the one hand, and nonlinear, self-organizing, and emergent complexity theory on the other. While readers of this journal are likely to be well aware of these changes, there is value in a careful examination of this apparent shift toward complexity-based inquiry in sustainability research. Indeed, there are dangers in not doing so: not only is conventional research growing more limited for revealing the nonlinear nuances that increasingly make up sustainability problems, but further, it may obscure the actual dynamics and dynamic elements in play in a given situation.2 Hence, there is a need to both distinguish the two approaches from each other, and to highlight how each may be better suited to address particular problemscapes, or econo-social-environmental systems situated in space and time.3 This paper attempts to address the above situation in three ways. First, in a brief review of current literature, it finds several types of confusion in conventional research and research calls. Second, it offers a distinguishing framework that clearly differentiates complexity-based sustainability from conventional views, and shows how both are valuable but each is incommensurable. Third, it presents an original, longitudinal and quantitative case study of a sustainability initiative in a UK organization, using competing hypotheses from each perspective. Results are unexpected and anomalous from a conventional perspective, but these “negative” findings may be interpreted as consistent with a complexity perspective on the organization and initiative. In sum, the neoclassical, positivist, and reductionist model of sustainability is certainly not the only, and may not be the best way to study internal organizational shifts towards sustainability. From literature to theory, and theory to practice, it appears that complexity perspectives are fast becoming the “there” needed in sustainability inquiry in order to get to the “here” of today’s sustainability issues and problems.”
Fritjof Capra speaks to The Heart of the Matter: A systems approach for achieving the UN Sustainable Development Goals.
“This is an urgent video message by Fritjof Capra, Ph.D., renowned physicist and systems theorist, about the critical importance of systems thinking as a means for achieving the UN Sustainable Development Goals (SDGs). The “heart of the matter” is the realization that our global problems are systemic problems — all interconnected and interdependent — and that the SDGs, therefore, must also be seen as systemically interconnected. Indeed, the shift from a fragmented, piecemeal approach to integrated, systemic solutions will be essential for the very survival of human civilization.
Four transformative actions are crucial to assure a sustainable future:
Shifting from quantitative to qualitative growth, inspired by the systems in nature.
Becoming ecologically literate in order to design sustainable communities;
Recognizing the nature of systemic solutions, with agroecology as an outstanding example; and
Adopting a new Earth ethics, such as the one summarized in the Earth Charter.”
That’s it for this week. Until next time - Ad Astra!