Phase transition afoot: decomposition, release and renewal

Patrick Hollingworth
October 29, 2020

Dear Reader,

I trust this writing finds you well. (Being well these days is, of course, a relative measure.) You may or may not have noticed how in my last piece back in May I subtly tried to kill off this newsletter, but it is back for at least one—in fact, no, make that two—more rounds.

The reason for its stay of execution is because there are so many dynamics currently in play that are manifestations of the things I’ve been writing about over the past half-decade and I feel like it’s too good an opportunity to miss. And so in this second-to-last missive (at least, second-to last in its current configuration), I want to touch again on issues relating to scale, because not only do I think they’re of prime importance right now, but I’m pretty sure that they will drive what will happen next.

My main thesis—which you’re probably very much aware of—is that we have recently passed through a complexity threshold that will be incredibly difficult—and more-than-likely impossible—to pass back through (remembering my previous reference to the work of Nobel Prize winner Ilya Prigione and the arrow of time). The way I see it, what will happen next is that things will fragment, decompose and release, prior to renewal (I’m referring to Buzz Holling’s adaptive cycle here, and touch on it in more detail later on). Many indicators suggest we are in the early stages of a meta-level societal phase transition, and my hunch is that it will play out over the next decade or so.

The root cause of this is that modernity—which at least in part gave rise to technology—has accelerated the progress of humanity too quickly. Our progression has happened so quickly that we’ve forgotten—or perhaps, willfully ignored—the things that we once knew, with these things being the things that kept our world in balance and in check.

The things I’m speaking about all manifest from wisdom, a wisdom which was accrued from many millennia of living locally and sustainably within the natural world. Tacit, uncodified and unstructured wisdom has its origins in praxis, and both require time to develop: thicker-duration temporal scales are key.

However, modernity has favoured knowledge over wisdom and shorter over longer timespans. Rapid diffusion of explicit, codified and highly-structured knowledge is now the currency of choice. As a scientist, I have no problem with this: knowledge based on empirical evidence gets the thumbs up from me. But highly-structured knowledge is at great risk of being too-far removed from its initial context, and the dangers of removing—or at least, over-simplifying, or misidentifying—context from knowledge are very real. (The (dis)United States of America is a prime example right now, but there are many other such examples lurking just out of site).

Context is what situates knowledge and enables us to learn and acquire wisdom. But knowledge without context is like a duck without a pond.

Remembering that there’s no such thing as a free lunch, it is an illusion to presume that rapidly diffusible, highly-structured knowledge is in and of itself a good thing. One must always pay the price for lunch, and as we are finding out in 2020, the price is rather steep.

A very expensive lunch, with idiots

The overt structuring and codification of knowledge is what removes friction and enables its rapid diffusion. My writing here is but one example: although it’s not too concise—I prefer to write long-form and give you space to reach your conclusions—it is structured in a way, using sentences and paragraphs and headings and so forth, that enables you to make sense of it relatively easy. It’s also sent via a technological medium—in this case, email and web browser—that makes it accessible to anyone on earth who can access the internet and is literate.

All good so far.

But what if what I am writing is completely bogus? What if it’s all bullshit? (It’s not, I assure you, but please bear with me).

This is the challenge that our modern society now faces: technology that enables anyone to say and do anything, and anyone with an internet connection to access it. We have removed so many of the scaffolding mechanisms that kept things in check, to the extent that any village idiot now has a platform to exhibit their idiocy to the world (and to join up with other village idiots, and form online communities). There’s nothing wrong with the village idiot—after all, every town has one—it’s just that in the past, everyone in each town knew who theirs was. These days its far less obvious—to some people at least—and they now host Facebook groups, blogs, podcasts and the like.

Modernity and technology: not good, nor bad

This is why I say that modernity and its associated technology is the key enabler of what is currently unfurling. Modernity and technology are not good or bad, they just are. In many, many contexts, they enable exceptionally good things to happen (i.e. improved health, increased standards of living, and reduction in poverty), but in many, many contexts they enable exceptionally bad things to happen (i.e. global warming, biodiversity loss, and the threat of nuclear war).

The key—I believe—to living with the amplified complexity that modernity and technology have enabled is to be appropriately wary of highly structured and codified knowledge that has been removed from its context, and to be unrelenting in the pursuit of the convexity and optionality which is found in tacit, less codified knowledge i.e. wisdom. By convexity I simply mean Taleb’s risk asymmetry i.e. limiting downside no matter what, but not limiting upside. That’s what wisdom—if correctly applied—does for you: it enables you to avoid the downside, whilst not capping the upside.

The role of wisdom

Now that our society has—in the pursuit of explicit, codified knowledge—done away with wisdom, we have also done away with the scaffolding mechanisms that used to keep society and human behaviour in check. Evidence of this is everywhere, perhaps none more so than in that we seem to be the only living species on the planet that continually shits in its own nest, and thinks that to do so in the pursuit of mindless, never-ending growth is entirely normal.

We’ve gotten our spatial and temporal scales the wrong way around

The advent of modernity and technology has given rise to the relatively recent concepts of globalisation and neo-liberal democracy and—without falling into the trap of describing them as pernicious i.e. we must remember that they are not good nor bad, it’s just context that makes them so—they have played a huge role in leading the world to the position that it now is in.

Globalisation has favoured global over local, neo-liberal democracy has favoured me over we, and the two of these forces combined have favoured today over yesterday, today and tomorrow. That’s why I describe these things as problems of scale: the first two relate to spatial scales and the latter one to temporal scales.

Pre modernity and technology, human society was comprised of diverse, heterogeneous small community populations and cultures naturally contained to local areas. These communities, often referred to as tribes, lived locally as multi-generational collectives. Not only were they multi-generational, they were intergenerational, meaning they understood the notion of long duration thick presents. Knowledge became shared wisdom from the combination of intimate, nearly infinite collective experience of the thick present gained in spatially limited locales.

Post modernity and technology, we have been conditioned to see the ultimate goal for human society as a homogeneous, global—soon to be inter-planetary—population and culture. Technology enables us—notwithstanding our current pause— to travel anywhere at will. We rarely live in multigenerational collectives anymore, and are encouraged to live in the moment, with scant regard for the past (and its long-earned wisdom) and for the future (because we believe that technology will solve all of our problems in the future). We borrow from the future, and see the present as instantaneous, not thick. This ultimately leaves us with a society which as a whole is fragile and lacking resilience, and is primed to fragment and release.

(When you think about it, it’s the message underlying the classic Mexican fisherman parable, which in itself is wisdom, not knowledge).

Adaptive cycles

The societal fragility and lack of resilience of which I speak—noting that I use both of these terms from a system level perspective (not from the more commonly used individual perspective)—is an indicator of where we are societally in Holling’s adaptive cycle.

If you’re not familiar with the adaptive cycle, it’s an ecology-based model which shows the non-linear dynamics of ecosystem evolution as things pull together, and then pull apart.

Holling’s adaptive cycle.

Attractor basins and phase transitions

From a technical perspective, a system—such as a society—is inclined to exhibit certain signals prior to a phase shift, the most apparent of which is critical slowing down. Critical slowing down occurs when perturbations of increasing frequency and deviation decrease the levels of stability within the system, which in turn leads to an elongated return-time to stability. This then leads to flickering —increasingly wilder swings, despite the noise parameter remaining constant—which occur as the system switches between different states at an increasingly rapid rate. 2020 is the year that nearly everyone begun to appreciate the true nature of these increasingly wilder swings.

With thanks to Joe Norman—who ran the simulation below of the simplest possible attractor dynamics—we can see how critical slowing down leads to phase transition. Although you don’t need to get hung up on the simulation’s formula (dx/dt + Lx + e(t)), the image below shows how a system approaches transition as the critical slowing down occurs:

Different attractor basins.

A negative value of the lambda value represents an attractor—also known as an attractor basin—where the greater the negative L value, the greater the attractor. The greater the attractor, the deeper the attractor basin, meaning the more stable and less dynamic the system. Therefore, in the above image L=-40 is the most stable, whereas L=-10 the system is far less stable, and L=0 is where all bets are off and the system’s reconfigurations are underway.

If this all looks and sounds too technical, it’s actually rather simple: the deeper the attractor basin, the greater the ease and speed with which things are pulled into it (and remain there). The less deep the attractor basin, the greater the resistance and slower the speed with which things are pulled into it (and the easier it will be for things to leave the basin).

If you’re struggling with this concept, just think of valleys, lakes, ponds and puddles: these are all manifestations of attractor basins (of varying depths), into which things i.e. water molecules, have been pulled by gravity.

Another way to think of it is to imagine a tennis ball being dropped into the deeper L=-40 attractor basin: the ball wouldn’t have much leeway to roll around. Imagine then the same tennis ball being dropped into the shallow L=-10 basin: the ball would have much greater freedom of movement. Finally, imagine the same tennis ball being dropped onto the flat L=0 surface: the ball could go anywhere.

If you’re familiar with any of the complexity-based frameworks such as Cynefin, perhaps the following figure laying out different domain types over the different attractors will help your comprehension.

Different attractor basins, and domains.

Thus, a stable system—such as a stable society—has deep attractor basins, whilst an unstable society, one that is beginning to fragment, has shallow attractor basins (which are becoming even shallower).

Wisdom erodes, via technology

A stable society is stable because the scaffolding mechanisms—which are roughly self-similar across each of that society’s different spatial scales—that have evolved over many, many generations keep the system (and the systems within the system, and so-on-and-so-forth) in check.

Thus, wisdom essentially creates and maintains deep attractor basins. What we are now seeing is the result of modernity and technology—the pursuit of context-invariant explicit, codified, highly-structured knowledge and the favouring of global over local, me over we, and today over yesterday, today and tomorrow—eroding these mechanisms and shallowing out these attractor basins. In other words, society’s L values are headed towards zero.

Thus, the dynamics of societal phase shift can be explained by this simple premise of flickering, critical slow down and the flattening of existing attractor basins.

What does a critical slowing down look like?

The two following diagrams illustrate a critical slowing down in two modelled scenarios. The first shows increased flickering and loss of stability from the attractor point (x=0), but no phase transition:

Critical slowing down.

The second shows a total loss of stability and subsequent phase transition, where the attractor x=0 becomes an unstable repeller i.e. rather than pulling things towards it, it pushes them away, further and further:

Phase transition is happening.

There are a couple of things worth noting here.

The first is that after a long period of stability, the gradual, almost unnoticeable changes in the first image deviate more and more. This is where a few non pattern-entrained people will start to identify slightly anomalous indicators—known as weak signals—and draw attention to them. These people—outliers—will be labelled doomsayers by the majority, and will be attacked and derided by any incumbents holding power who are likely to lose that power after the phase transition. Consider me to be one of these non pattern-entrained outliers, and my writing to be a weak signal.

The second thing worthy of note is the sheer speed with which the irreversible, non-linear collapse of normality occurs once the threshold is breached in the second image.

Banging on: radical interconnectivity and interdependence

Human systems are now so radically interconnected and interdependent—not only with each other, but also within the global natural ecosystem—that there is no avoiding this phase transition. The threads of this rich, multidimensional tapestry are pulling apart (as they always have done), before they reconfigure (as they always have done).

It’s inevitable, because everything evolves.

All you can realistically do is understand what is happening, as it is happening—this will at the very least reduce your cognitive dissonance—and if you’re lucky and savvy enough, move when the upside opportunities present. (Being able to see these opportunities as they approach is one of the main things I teach; see at the bottom for details of two courses I’ll be running in New Zealand in 2021.)

If you’re a regular consumer of my writing, you’ll be aware that I’ve been banging on about these dynamics for many years now. (If you’re not a regular consumer, then it’ll help you to read this  this, and this piece to bring you up to speed.) You’re also no doubt bored to death of me labouring their underpinnings—interconnectivity and interdependence—and why it is so important to understand the entirely new ontology of complexity that interconnectivity and interdependence create.

(That’s one of the reasons why this newsletter is itself undergoing a phase transition: it’s simply following the adaptive cycle, and having reached its maximum state of conservation, its collapse, release and decomposition is underway. I’m looking forward to sharing some novel recombinations with you at some point in the future.)

(After) what happens next

Precise prediction in complex systems is a mugs game, so you’d be a fool to try and predict exactly what will happen next and exactly when it will happen (rather than prediction, learn to see patterns and dynamics). All you can be sure of is that something will happen. Something—in fact many things—are already happening.

My intuition—noting that this is not a prediction, but rather emergent patterns I am sensing—is that new attractor basins around localism, the collective and intergenerational, longer temporal scales will begin to form (paradoxically at larger scales, because they already exist at smaller scales). I also sense that a renewed appreciation of tacit wisdom—not only that of traditional, indigenous cultures, but also the inherent wisdom of the natural world itself—will create additional attractor basins.

I am of course biased: after-all, my intuition guides me. But it is these concepts—or rather, these fragments worthy of bricolage—of localism, the collective, intergenerational temporalities, and tacit indigenous and natural wisdom, which have me excited over the longer term.

What happens in March 2021: exciting learning courses in the mountains!

One prediction that I can make is something that I’m running in March next year, and in which you might be interested.

Over the past decade I’ve conducted learning courses in the Stirling Ranges in Western Australia, the Central Highlands in Tasmania, the Southern Alps in New Zealand, and the Himalaya in Nepal. Over the course of a week or so—or three weeks, in the case of the Himalaya—we do something of a ‘deep immersion’ and head into a remote mountain locality where we use the landscape (and our movement through it) to explore the foundational components of complexity, networks, ecosystems, culture and narrative, knowledge dynamics, and system reconfigurations.

Visibility of landscapes and systems in Mount Aspiring National Park.

Intended for professionals and students that want to establish an understanding and intuition of complex social and organisational systems—and how they can apply this to real world problems—it’s a course which teaches science and exploration (not philosophy and tourism). I like to keep the groups small and intimate, and they tend to be pretty rich and powerful learning experiences. Although it involves movement through mountain terrain, it doesn’t require any technical skills (although a base level of fitness is needed).

A relatively shallow attractor basin in Mount Aspiring National Park.

Next year, I’ll be running two such courses in the South Island of New Zealand, both in March. I’m fortunate in that we have a small base to operate out of: it’s at the top of a beautiful lake and adjacent to a glorious 3,562 square kilometres of wilderness in the Mount Aspiring National Park.

From the top of the lake we go.

Over the past few decades I’ve gotten to know this landscape pretty well, and in addition to the opportunities it provides for deep learning, it is one of the most stunning mountain landscapes in the world (and trust me, I’ve been to a lot of mountain landscapes over the years).

Of course, my prediction fails if pandemic-associated border closures remain, so for now the course will only be open to participants currently living in Australia and New Zealand. If borders have not reopened between these two countries by late February, we’ll cancel or postpone the courses and you won’t be charged.

For detailed information on the course timing, structure, topics covered and costs, please visit this link.

With thanks,

Patrick

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