As I’ve mentioned in earlier posts, if there’s any system-y description that captures what is happening with the global COVID-19 pandemic, it’s basically that the world is having its bell rung. Traveling conveniently in literally a matter of days/weeks/months (the final answer is still unknown) as far as spread, in certainly a geological short amount of time, the pandemic is seemingly everywhere. Organizations like Yaneer Bar-Yam’s New England Complex Systems Institute, as well as universities like John Hopkins, produce charts of various infection rates, death rates and such, and map these things with little lag (varying in both accuracy and reliability dependent on source) across the Internet.
It’s almost like watching a deadly soccer game. Or more aptly, a big wave surfing competition. The different countries get on waves of different heights, dependent on a variety of factors, and surf down them until the wave dissipates, or they decide to bail off. The absolute score is the % fatality rate, when normalized with population, and there are definite winners and losers. So far, the U.S. is deep into Kook territory, though the Russians aren’t far behind.
In systems dynamics parlance, such an impulse of magnitude is akin to a Dirac Delta, or Impulse function, which is how, when we want to characterize harmonic response of a system, we whack it with a figurative, or often literal hammer. And then we watch how it oscillates, seeing which frequencies die out more quickly or less quickly. Plots of the resonance are made, and the modes of oscillation are constructed.
Underlying all this is an assumption of linearity. But linearity doesn’t mean what most of the public assumes it means. What it means is that each of the independent fluctuations at a given frequency that we see is uncoupled from other fluctuations. There are no meaningful interactions between one oscillating trend and another. When you whack a beam with a hammer, you get a primary resonance at the natural frequency of the beam, which is some combination of length of the beam, how it’s supported, and whatnot. But you also get a resonance at 2x, 3x, 4x in the frequency domain. And here’s the key. Even though these resonances are multipliers, if you damp out one, it doesn’t necessarily change the amplitudes of the others at other multiples. They are independent of each other. Believe it or not, that’s what vibrations people call linearity.
Such is NOT the case with large scale social/psychological/economic systems. The COVID-19 hammer comes down, mostly delivered by our air transport system and a cruise ship or two, and maybe a nightclub DJ. “Bong” goes the system, and the odd advantage of this particular pandemic, in a nation, or really a global system that seems far too unaware that we actually already had problems in multiple areas (like diet, health care, employment security and some such) all of the sudden, the public, via the Internet, is grossly aware of lots of things happening.
The public, networked together via the Internet, is a wildly imperfect sensor network to observe this response. The individual sensors are limited by all the things we normally think of when we pick sensors for far simpler applications — sensitivity, range, temporal scale and spatial scale. Those sensors themselves have frequency response characteristics that in more traditional applications (like whacking beams) we compensate for on the backside.
But we live in a global society, unaware of its deeper structural memetic makeup. And in fact, even bringing that up, outside our tired, tread-worn models of culture, national identity, income and education, are perceived as being positively reprehensible by the sensors, er, people themselves. Such is the curse of the post-modern world. The virus crept up on us without any ability to calibrate. How many people die in nursing homes, anyway? How does the immune system actually work? Answering these and a myriad other questions are happening real-time. COVID-19 has the characteristics of what we call in surfer-ology a Sneaker Wave. Such a wave appears out of nowhere, out of the normal stack of colds, flu, and cancer, and can wash you out to sea.
But back to banging the gong. COVID-19 is profoundly testing the resilience of modern society. And regardless of the sensationalist press, modern society is holding up reasonably well — for now. There are lots of cracks appearing in the infrastructure, and there may indeed be collapse in our future. I’m not ruling it out. But compare modern society and our death tolls to the Bubonic Plague in the 14th Century. There is simply no comparison. We are not dragging people outside the city walls, half alive, to die in the fields alone. We are not throwing hundreds of thousands of bodies into lakes because we cannot bury our dead. None of this means, of course, that what IS happening is what we should aspire to. Far from it. For the means that we have as a nation and a world, we can, and MUST do better.
But doing better can only be done incrementally now, in the middle of the crisis. We can search for opportunities for better care for threatened, immunosuppressed populations. We can make sure people have plenty of food, and employment security. Large-scale system overhaul is going to wait, whether it fits in with our aspirations or not.
And this is where ringing the bell can help. I am proposing a new way of understanding this pandemic, from a deeper structural memetic perspective. We have myriad information streams, that we associate with topical relevance. But these streams actually contain different structures, varying from simple to complex. Understanding their decomposition matters. How, for example does opening up turn into “only money for the rich” as opposed to “support for community business”? What’s the emotional content? How long did it take the complexity to dissolve into our boxes? I just read a paper on baseline memes by Ugo Bardi that looked at simple memetic fragments around Greta Thunberg. Maybe it’s time to get some better algorithmic thinkers than myself involved in quantification of these things.
There are other things to look at. One of the characteristics of nonlinear systems is that cycles of different frequency and wavelength are often coupled together through various nonlinear functions. In my past life, I did extensive analysis of bispectral and trispectral coupling of these types of systems. These types of analyses look at coupled phase lag between different parts, and creates a causal function between two dissimilar parts of a frequency spectrum coming out of an excitation like whacking the system with a hammer. So instead of a peak you see sitting on its own, in isolation, it turns out it’s actually tied to a bunch of other peaks. And if you push down on those other ones, the main one also starts to recede. The time scales are different, and the connection not immediately obvious. But you can still potentially affect the problem you’re focused on from a distance, in another system. That’s the big point here.
One can easily extend this in the information space to the COVID-19 meta-crisis. We are going to be awash with data of all sorts, in all fields, of events and their timing, and their effects on all of our different social systems. It could be a true transdisciplinary endeavor. Every discipline knows about how they collect information. Every discipline could give in a little to create quantification schedules for events and their timing, and watch the various trends rise and fall. It’s more complex AND complicated that just looking at a simple time series analysis that some moke like me might do on a simple mechanical system.
But it could suggest how we explore linkages, and create whole new, more enlightened fields of public policy. These are things that are going to demand rigor, of course. But considering we have such a poor understanding of even basic things — like how diet actually affects health outcomes, or even the way we think — it could be revelatory. Death is terrible — but it’s also hard data.
If there’s a path toward doing this, it’s got to start with understanding ourselves first. I’d argue we really need to understand the DeepOS of how we know on this blog, and look not just at our old, hidebound, and largely irrelevant models. The stereotypes of culture don’t hold up in a modern globalized world. We can look at knowledge structures, and we can start the process of quantizing much of the work that I’ve started on these virtual pages. Instead of constantly, chronically dividing and intersectionalizing, let’s look at ways of finding commonalities and meaningful differences between people. I read anthropology papers about tribal people in various parts of the worlds, along with the authors’ desperate attempts to generalize things seen at the tribal level in modern society. And while I am all down with a groundswell of support for human dignity, there are differentials that make it possible for people to build skyscrapers. We don’t understand that level of social organization at all. Or rather, we gloss over the fact that the effort may have changed us. Even though it clearly has — so let’s map both.
A glossary of concepts regarding nonlinear systems, applied to sociological concepts would also help. There’s a natural tendency in the liberal arts to deconstruct until one gets back to the same set of white guys. It’s all about giving credit, rather than creating insight. I totally believe in learning from the greats in the past. But there is a new complement of tool sets out there. We don’t insult the past giants by standing on their shoulders. I’d like to think they expected us to innovate as well. Correctly using nonlinear systems concepts would be a big step in the right direction. The field is literally only about 100 years old, a babe in the mathematical sense. Let’s do a reframe of our problems.
Finally, let’s not blow this opportunity. I hear lots of people talking about a ‘new normal’ — and the ‘new normal’ that people proposes looks a whole lot like the old normal, except more repressive. I see lots of bright possibilities in the future. But they are going to demand, across all our institutions, and especially the academy, changes toward connection and personal development. The endless fractionation isn’t working folks. It’s time for all of us to focus on growing our empathy.
A better and more rational world awaits. All because we got our bell rung.
14 thoughts on “Ringing Global Society’s Bell — Potential Learnings from the COVID-19 Epidemic”
I’ve been discussing via email about writing a curriculum on complexity theory with someone who has a loose connection with SFI—he’s a teacher of k-12 teachers and thinnk they should be teaching some complexity theory. (There are actually about 20+ people who theoretically are contributing to this, from k-12 teachers, grad students, a few philosophy prof types, etc. Most of them really are not active.
Nothing may come of this—people can’t even agree on a definition of complexity–they say nonlinearity is involved, but many can’t even define that. (I personally want it to be some thing that goes from 0 to 100—ie somehing for the pre-K set all the way up to post-doc/research set—something at every level and people can choose where to start and how far to go. eg they can have a bike trip using trailer wheels, or they can do the Tour de france or a wilderness mountain bike trip. only bike trips i’ve done are ;’in between’—i have done 150 miles/day but i’m not competetive—i just take my time; and i do go off road when i have a working mountain bike (someone basically stole the one i had—i loaned it to someone who did not return it.) but i don’t do these extreme mountain bike tris—you need a 1000$ bike to do those. my bike wouldn’t make those trails. i walk them and hide my bike—i can’t afford to buy a new bike every time i take a bike trip.)
https://sciencehouse.wordpress.com is another blog (by a math biologist at NIH trained in physics) which deals with COVID. discusses many of the (often partly contradictory models. i think there are over 5000 academic papers on Covid last 4 months –maybe 500 + of them math models. arxiv lists them, and AAAS has its own archive and there are more–which overlap. i disagree with some of his views on behavioral genetics (he linearizes alot gene-environent interactions out. he’s written paper his stephen hsu, jack cowan and others on genetics, neuroscience, etc. He’s also an expert in ‘obesity’ theory. )
Y bar- Yam’s (i can never remember the spelling) model i don’t think is linear. its more like a netowrk or ecosystem model.
Your example of decomposing a system into ‘harmonics’ is often approximately true and this is often done for nonlinear systems–you linearize them.
there are some books which go through the tehnical issues regarding non-lineairty (eg Bruce West’s book ‘on nonlinearity’ he’s a well lnown physicist and a devout militarist—that’s who employs him—and semi-‘climate denialist’. his colleague who was at Duke physics (since returned to italy) has lots of papers which claim global earming is essentially a linear superposition of solar cycles.) .
many of the books/paper on nonliear systems are written in theorem-proof style. above my pay grade., but the other versions are often hand waving—eg they say nonlinear systems are not ‘mechanical’ or newtonian. the newtonian 3 body problem is chaotic and nonlinear. people are mixing memes, genes, apples, oranges integers, primes, real and complex numbers and trying to add them up. .
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Well, er, um. I lost that email address you gave me. Sort of. I mean, I “deactivated” my Twitter account, which I could easily reactivate. But I don’t want to? Plus I knew I could find you here.
Meanwhile, you can find me, if desired, via the links/email given via this comment. I’d very much like to help you publish your book, whatever that might turn out to mean. Also, I mentioned you in a recent post: https://dhyoung.net/2020/05/24/epiphanies-and-apostrophes/
So there’s all that.