COMPLEX VS COMPLICATED

EPISODE 3 MUSIC IN PHASE SPACE

WHAT DOES COMPLEXITY MEAN?

The nature of the scientific problem here is strongly analogous to that of complexity in physical systems. The elegantly simple formulas of Newton’s laws of mechanics make it relatively easy to calculate the orbits of two heavenly bodies once we know their respective masses and the distance between them. Add one more body, however, and the calculation of orbits resulting from the interaction becomes far more complex. When there are ten bodies interacting (this is the simplified version of our solar system),no orbits ever exactly repeat themselves, and there is no way to predict the long-term state of the system. As each new variable is introduced, the number of ramifying interactions to be taken into account grows geometrically.

James C Scott-Seeing Like A State

REDUCTIONISTIC

Science has progressed by always being reductionistic: that is, reducing things to their primary elements, whether they’re electrons, atoms, molecules, or genes and so forth. That has been enormously successful, but one of the things that we’ve begun to appreciate more and more is that kind of paradigm has extraordinary limitations.

When you try to build up from these fundamental elements to the collective whole, you discover that the whole is much greater than, behaves differently than, and is structured differently from the sum of its parts. What you recognize in parallel with that is almost all of the major issues that we face on the planet — everything from climate change and the question of stability in markets to potential questions about risk and how we deal with things like cancer, and the encroaching threat of global urbanization — are what we call complex. They’re not easily, or even potentially, reduced to the sum of their parts.

Organisms like you and I are much more than the sums of our cells or genes. A city is much more than the sum of all its people or roads and businesses. Furthermore, all of these are not just conglomerations of all of these things: They’re all highly dependent upon one another. There’s what we call express emergent properties: New things emerge as you build these systems up, whether they are economies, climates, cities, or our bodies.

Complex and Complicated

Sending a rocket to the moon and surgeons extracting brain tumors are complicated tasks while getting children to succeed in school (or, for that matter, raising a child) and the climate are complex. The simple metaphor you could use to explain complexity versus reductionism is something like that. The study of the dancer is reductionism. The study of the dance is complexity.

The dance is something that is kind of playful, it’s organic, it’s not a recipe. It has structure, but it’s not sort of prefab. I think that’s so much of what we experience in the world is really the spontaneous kind of like playing a game or dancing. We don’t really have a great handle on that. In fact, even the structure of formal systems proper don’t play well, in a crucial way, with that kind of spontaneous playfulness that we actually observe in the world.

Complicated

Complicated procedures like brain surgery and rocket launchings require engineer-designed blueprints, step-by-step algorithms, well-trained staff, and exquisite combinations of computer software running carefully calibrated equipment. Think rocket landing on the moon in 1969, doctor-controlled robotic arms doing brain surgery.

A complicated system assumes expert and rational leaders, top-down planning, smooth implementation of policies, and a clock-like organization that runs smoothly. Work is specified and delegated to particular units.

Certainty about outcomes is in the air the organization breathes. Complicated systems use the most sophisticated math, technical, and engineering expertise in mapping out flow charts to solve problems.

Yet even those sophisticated systems fail from time to time such as the Challenger shuttle disaster, Three Mile Island nuclear meltdown, and the 2010 BP oil leak.

Complex

A typical complex system is composed of myriad individual constituents or agents that once aggregated take on collective characteristics that are usually not manifested in, nor could easily be predicted from, the properties of the individual components themselves.

For example, you are much more than the totality of your cells and, similarly, your cells are much more than the totality of all of the molecules from which they are composed. What you think of as you — your consciousness, your personality, and your character — is a collective manifestation of the multiple interactions among the neurons and synapses in your brain.

Complex systems like are filled with hundreds of moving parts, scores of players of varied expertise and independence yet missing a “mission control” that runs all these different parts within an ever-changing political, economic, and societal environment. The result: constant adaptations in design and action. Recall a band, a record label, streaming services and scores of interest groups trying to get a reform of a system in collapse during the 2010s in the midst of a slow recovery from the quasi-Great Depression of 2008.

Complexity is really about the way interactions give rise to phenomena.

Not only are we moving beyond reductionism in terms of emergence of novel properties, but also the way that whole systems, say a single organism, give rise to what we can part out and analyze as the parts of the system.

An organic and growing complex system develops and will actually synthesize its own components, functional components, etc. This is very much beyond what reductionism as a philosophy can really speak to.

Blueprints, technical experts, strategic plans and savvy managers simply are inadequate to get complex systems with thousands of reciprocal ties between people to operate effectively in such constantly changing and unpredictable environments. These web-like complex systems of interdependent units adapt continuously to turbulent surroundings

Music, the music industry and touring— even with their façades of command-and-control mechanisms and policy manuals filled with procedures for subordinates to follow — are constantly buffeted by unpredictable events.

A car is complicated, traffic is complex. You can build a car or repair it, but you have to manage traffic. You can achieve full visibility of a complicated system but not of a complex one. That’s why rules can be used with the former but not with the latter.

One practical outcome of this distinction is approaching planned change differently. Those who run complicated systems (e.g., airplane and automotive industrialists, investment bankers, computer hardware and software CEOs) introduce change by laying out a detailed design of what is to be changed, step-by-step procedures to implement the change and overcome any employee resistance, and reduce variation in performance once change is implemented. Highly rational, mechanical, and smooth.

The problem for those who inhabit complex systems like schools is that change, conflict, and unplanned changes occur all the time. So do adaptations because of the web-like independent and interdependent relationships that make up the system. What happens when smart people try to graft procedures from complicated organizations onto complex systems?

The answer, then, to the so-what question is: At the minimum, know that working in a complex system means adapting to changes, dealing with conflicts, and constant learning. These are natural, not aberrations. Know further that reform designs borrowed from complicated systems and imposed from the top in complex systems will hardly make a dent in the daily work of those whose job is convert policy into action.

GENIUS

While it is not necessary to be a genius to manage complexity, it is helpful to consider for a minute the difference between a genius and someone who is really smart. The reality is that Einstein thought differently. A little-known fact is that most of his mathematical problems were solved by others, including an assistant, Walther Mayer, who solved many of the mathematical equations and did most of the calculations that Einstein’s musings required. Einstein was a complexity thinker, while Mayer was a very good and very intelligent complicated thinker.

LIMITING PARADIGM

It’s the “when the only thing you have is a hammer, everything looks like a nail” syndrome. This usually means it is time to design new epistemological tools. On the other hand complex adaptive systems thinking might be responsible for the fact that today we confront exponential escalation. Here everyone and everything both struggle to adapt to continuous pressure, and in the process exerts continuous pressure on every other agent to adapt. Think of antibiotics and bacteria, insects and pesticides, markets and trade, nuclear arms and defense.

It seems that every adaptive response we make, only makes matters worse. Every contributing factor we discover, only makes understanding more complex.

Guitar Knobs

I recently got a new Gibson SG with the coil tapping feature where I can use each of the two pickups as either single coil or humbucker by pulling up or pushing down on the volume knob for that pickup.

Suppose you have a guitar with only high and low knobs. Then you can’t set the qualities you want directly. Instead you fiddle with the high and low knobs to find the settings that create the guitar you want.

The overwhelming practical issue is that when you have millions of “guitar knobs,” you can’t readily calculate the ideal positions for them all. A landscape can sometimes be too complicated to evaluate comprehensively. You can only make progress by starting at one point on the landscape and then tweaking inputs incrementally to see if the goal you seek seems to be furthered.

You crawl on the landscape instead of leaping. In other words, your best bet is to move guitar knobs a little bit at a time to see if you like the result better. You can’t really explore every combination of guitar knob positions in advance because that would take much too long.

This is also how evolution works. Evolution is dealing with many billions of “knobs” in genomes. If some new genetic variation reproduces a little more, it gets emphasized. The process is incremental, because there isn’t an alternative when the landscape gets extremely big and complicated.

Usually a landscape is imagined so that the solution sought would be the highest point on it. The eternal frustration is that incremental exploration might lead up to a nice high peak, but an even higher peak might exist across a valley. Evolution takes place in millions of species at once, so there are millions of explorations of the peaks and valleys. This is one reason why biodiversity is so important. Biodiversity helps evolution be a broader explorer of the gigantic hidden landscape of the potential of life.

CONTROL

“All those buttons and levers that are theoretically on your desk? Most of them aren’t connected to anything!” Right? You can press all those buttons, pull all those levers, not a goddamn thing will happen because the corporate equivalent of deep state will keep on doing what it’s doing in its own self-organizing, self-interested agency risk fashion.

And if they do manage to do anything at all, as you mentioned, most likely whatever those consequences are will be unintended ones, as opposed to whatever that executive imagined the effect would be. We just have so many interdependencies, and subtle effects in variables, and unidentified relevant variables, etc. So when you pull on that lever, you think A is going to happen, and maybe it happens, maybe it doesn’t happen, but you often get X, Y, and Z instead.