Machine. Ecosystem. (8) – classrooms as complex adaptive systems

Planning is essential in education, but it’s easy to fall into the habit of treating your session plan or presentation as a set of inputs for a machine: “If I do these things, and introduce this content, and prescribe this activity, this learning will result.”

But we know that groups of people, and especially groups of children, don’t work so predictably. The ‘perfect’ lesson plan a classroom is a Russian doll of one set of complex adaptive systems inside another inside another:

  • The rapidly developing minds of children or teenagers…
  • Nested in expectations and the social structures and groups-within-groups of kids-at-school culture…
  • In the classroom culture shaped by a particular teacher – who is themselves a complex adaptive system of body, thoughts and emotions…
  • Interacting with the wider culture of the school…
  • All interacting with cultures local, national and international…
  • And influenced by what’s going on at home, the weather, what they had for lunch…

In the face of this complexity, the first thing to do is recognise that what happens in our classroom is beyond our control, at least in the mechanistic sense of the word. Trying to impose precise control – of learning outcomes, of students’ behaviour – is a recipe for frustration and disappointment, if not damage.

The second thing is to start thinking about teaching and classroom management in terms of disposition and influence (and teachers can have a lot of influence):

  • How can I make it more likely that the people I teach arrive on time and ready to learn?
  • How I can I increase their disposition to be kind to each other, or to love this subject and to work hard?
  • How can I make it more likely that they’ll do X, rather than Y?

Go to work. Take responsibility. Do the hard work of building a classroom culture that gets your students where they want to go (hint: you might have to start by showing them where it’s possible to go).

But don’t beat yourself up the next time it snows, and the lesson plan goes out the window as the kids pile up against the window to watch the world turn white.

A butterfly must have flapped its wings in New York.

Tim O’Reilly on structural literacy

Access to an unlimited world of information is a powerful augmentation of human capability, but it still has prerequisites. Before she could make an exquisite dessert by watching a YouTube video, my stepdaughter had to know how to use an iPad. She had to know how to search on YouTube. She had to know that a world of content was there for the taking. At O’Reilly, we call this structural literacy.

Users without structural literacy about how to use computers struggle to use them. They learn by rote. Going from an iPhone to Android, or the reverse, or from PC to Mac, or even from one version of software to another, is difficult for them. These same people have no trouble getting into a strange car and orientating themselves. “Where is that darned lever to open the gas cap?” they ask. They know it’s got to be there somewhere. Someone with structural literacy knows what to look for. They have a functional map of how things ought to work. Those lacking that map are helpless.

The level and type of structural literacy required differs with the type of work you do. Today’s startups, increasingly embedding software and services into devices, require foundational skills in electrical and mechanical engineering, and even “trade” skills such as soldering… Teachers are far more effective if they are broadly familiar with the culture and context of their students.

Tim O’Reilly – WTF?: What’s the Future and Why It’s Up to Us

Machine. Ecosystem. (7) – Style is content (text as system)

Style is content.

Poet Marvin Bell reminds us that the content of a poem is not the same as a poem’s contents, reminding us that when we paraphrase what a poem is about (its contents) we are not talking about the poem itself (its content or meaning), losing sight of what it does to us as we read it. The same is true of sentences.

Or, to put this another way, the informational or propositional content of a sentence is not the same as the sentence’s meaning, since sentences don’t just carry information, like putting objects in a canister, but do things with it and to it, shaping it to particular purposes and effects. In this important sense, sentences work like verbs, doing things, taking action, rather than like nouns that only name.

Most of us have been taught to think of style and meaning or form and content as two different things. We think of content as the ideas or information our writing conveys. We think of style as the way in which we present those ideas. Many aphorisms and metaphors have been used to describe style, ranging from “Style is the man himself” to “Style is the dress of thought.”

If we have to use a metaphor to explain style, we might think of an onion, which consists of numerous layers of onion we can peel away until there is nothing left—the onion is its layers, and those layers don’t contain a core of onionness but are themselves the onion.

Brooks Landon – Building Great Sentences: Exploring the Writer’s Craft (amazon)

He’s right, of course. I’m not ready to dismiss propositional content just yet, but the danger more often comes in the opposite direction, as we try to reduce the irreducible, rather than living with complexity.

Texts are complex adaptive systems: the whole is more than – and different from – the sum of the parts. They change, too, as the meanings, ideas, feelings that we bring to them change. They change even as we read them, because we’re changed by the very act of reading.

If it’s nonsense to speak of the meaning of words outside of text, or of sentences in isolation, then it’s nonsense to speak of trees apart from forests, or people in isolation from their contexts, or cars in isolation from the ecosystem that they’re part of.

And yet… we do, and frequently find it useful or necessary to do so. The important thing is to see that the lines we draw are arbitrary (although some work better than others). The best we can do is try to hold the whole in mind even as we think about the parts, avoiding both the trap of mechanistic, reductive thinking, and the equal-and-opposite trap of of using complexity as an excuse to avoid the hard work of paying attention to detail.

Kicking cans: job descriptions versus culture

A few days ago I watched a schoolboy kicking a can down the road. He kicked it a couple of times and then miskicked, sending the can flying into the road, where it landed at the feet of an off-duty city cleaning worker, still in his orange uniform. These guys are fantastic: they put in the hard yards of sweeping the streets, cleaning out ratty drains and fetid canals doing a whole load of other stuff to keep Jakarta clean. This guy – in his uniform – trapped the can with his foot, bent down, picked it up, and looked at the kids with a grin that said “Don’t worry guys, I’ve got this.” Then he leaned back and tossed the can stylishly over his shoulder and straight into the… flowerbed.

This is a man who spends several hours a day sweating to keep Jakarta clean. He works in the dirt and grime, puts up with rats, cockroaches, heat and traffic fumes to clean the city up and to keep it clean. He’s part of the Orange Army transforming Jakarta – but he throws a piece of rubbish that lands at his feet into the flowerbed instead of the bin. Why?

Because that’s his culture. It’s what he saw his parents do, it what his neighbours do, and despite the best efforts of the school curriculum to teach another way, it’s probably what his kids do.

Job descriptions alone won’t solve this problem: you can hire all the street-sweepers you want, but you’ll never have clean streets until a large majority of people put their rubbish in the bin rather than throwing it on the ground. In other words, until keeping the city clean becomes the culture: “people like us, do things like this.”

Changing the culture is harder work than giving some people the job of cleaning up everyone else’s mess. Harder and slower, but in the long run more effective, cheaper and more sustainable. Changing the complex system of culture takes conversations, campaigns, and curriculum changes. It takes leadership: politicians, celebrities and parents who care enough to do what they say. And it does need street sweepers – people can’t see that the streets are dirty until they’ve seen clean ones.

Job descriptions are necessary, but they’re never sufficient.

*See also: Singapore, tree planting and the new normal

Machine. Ecosystem. (6) – Kevin Kelly on the techium

Okay, so machines are simple, largely linear, and predictable, and systems are complex, adaptive and ‘dispositional’… but look a bit closer and the distinction gets blurry.

Most systems (individual people, markets, forests to name three) are combinations of sub-systems that are, at the end of the day, made up of simple units. And our machines – especially digital ones – are increasingly complex and interconnected. Even our simplest machines don’t really stand alone – they’re outgrowths of human activity, the product of networks of ideas, activities and resources that allow them to develop, grow, and – if they’re not maintained – fall into obsolescence and decay.

Kevin Kelly calls this the techium*, and describes it brilliantly in What Technology Wants:

Once [19th century economist Johann] Beckmann lowered the mask [of technology, by uniting various arts and sciences under the term technologie], our art and artifacts could be seen as an interdependent components woven into a coherent impersonal unity.

Each new invention requires the viability of previous inventions to keep going. There is no communication between machines without extruded copper nerves of electricity. There is no electricity without mining veins of coal or uranium, or damming rivers, or even mining precious metals to make solar panels. There is no metabolism of factories without the circulation of vehicles. No hammers without saws to cut the handles; no blades without hammers to pound the saw blades. This global-scale, circular interconnected network of systems, subsystems, machines, pipes, roads, wires, conveyor belts, automobiles, servers and routers, codes, calculators, sensors, archives, activators, collective memory, and power generators – this whole grand contraption of interrelated and interdependent pieces forms a single system.

When scientists began to investigate how this system functioned, they soon noticed something unusual: large systems of technology often behave like a very primitive organism. Networks, especially electronic networks, exhibit near-biological behaviour.

Kevin KellyWhat Technology Wants (amazon)

In our organisations, this way of seeing helps us to think about the machines we buy buy of the networks of activity and supply that are necessary to maintain them and run them well – a way of thinking that’s probably automatic in the manufacturing and computer industries, but comes far less naturally in the social sector.

Something as simple as buying a new computer or printer isn’t just that simple. It’s introducing a new organism into an ecosystem, and will require our teams to do the work of acclimatising and adapting to make it really useful. The more complicated or relational a technology is – social media being a prime example – the further the adaptation and unintended consequences go.

*as distinct from specific technologies

Machine. Ecosystem. (5) – Duncan Green on systems thinking and development

A ‘system’ is an interconnected set of elements coherently organized in a way that achieves something. It is more than the sum of its parts: a body is more than an aggregate of individual cells; a university is not merely an agglomeration of individual students, professors, and buildings; an ecosystem is not just a set of individual plants and animals.

A defining property of human systems is complexity; because of the sheer number of relationships and feedback loops among their many elements, they cannot be reduced to simple chains of cause and effect. Think of a crowd on a city street, or a flock of starlings wheeling in the sky at dusk. Even with supercomputers, it is impossible to predict the movement of any given person or starling, but there is order; amazingly few collisions occur even on the most crowded streets.

In complex systems, change results from the interplay of many diverse or apparently unrelated factors. Those of us engaged in seeking change need to identify which elements are important and understand how they interact.

Unfortunately, the way we commonly think about change projects onto the future the neat narratives we draw from the past. Many of the mental models we use are linear plans – ‘if A, then B’ – with profound consequences in terms of failures, frustration, and missed opportunities [when the plan is thrown out by unexpected consequences within the plan, or by things that were never in it]. As Mike Tyson memorably said, ‘everyone has a plan ’til they get punched in the mouth.’

Let me illustrate with a metaphor. Baking a cake is a linear, ‘simple’ system. All I need to do is find a recipe, buy the ingredients, make sure the oven is working…

Baking a cake is also a fairly accurate metaphor for the approach of many governments, aid agencies, and activist organisations. They decide on a goal (the cake), pick a well-established method (the recipe), find some partners and allies (the ingredients), and off they go.

The trouble is that real life rarely bakes like a cake. Engaging in a complex system is more like raising a child. What fate would await your new baby if you decided to go linear and design a project plan setting out activities, assumptions, outputs, and outcomes for the next twenty years and then blindly followed it?

Deng Xiaoping said, “We will cross the river by feeling the stones under our feet, one by one.”

Duncan Green – How Change Happens (amazon)

Machine. Ecosystem. (4) – Marc Andreessen on Systems Thinking

Think about it [systems thinking] through the lens of a new tech product, which is kind of the centre of what we do [at Andreesen Horowitz]… If you’re not a systems thinker basically you say “I’m going to build a really great product, and then I’m going to have a really great product, and it’s going to be great, because it’s a really great product.”

The systems thinking more is that that’s just the first step because it’s not just about the product. It’s about okay, now the product is going to enter into the marketplace, and there are going to be customers that are going to have a point of view on your product, and there are going to be competitors that are going to be trying to take you out with a better product. And you’ll put your product in retail, and the retailers are going to try to gouge you on price, and make your product uneconomic to manufacture, and the press is going to write a review of your product, and maybe the reviewer is going to have a really bad day and he’s going to say horrible, horrible things… and your employees are hard at work and they build the first product, and you assume they’re going to be with you to build the second product, and maybe they will, or maybe they won’t, because maybe someone else will hire them.

And so with any kind of creative endeavor, with anything we do in our world – and this is for products or for companies – they’re launching into technically what is called – there’s actually a mathematical term – a complex adaptive system – the world. And inherently it’s not a predictable system, it’s not a linear system, it doesn’t behave in ways that you can expect, kind of by definition. So they say “complex” because there are many, many dimensions and variables, and then “adaptive”, like it changes. Things change. So the introduction of a new product changes the system and then the system recalibrates around the product.

And so as a consequence, to launch a new tech product and have it succeed you have to have a keen awareness of all the different elements of the system. You have to have a willingness to engage in the entire system, and it’s a gigantic problem generally if you’re in denial about that, if you’re not willing to think in systems terms.

Marc Andreessen on The Moment with Brian Koppelman*

*Full transcript here.

Machine. Ecosystem. (2)

Yesterday’s post laid out several reasons benefits of understanding your organisation as a machine.* But many of the important parts of your organisation don’t behave in predictable or mechanistic ways. Your team’s culture, for example, is a affected by, for example:

  • organisational history;
  • personalities on the team;
  • individual moods;
  • collective morale;
  • Team members’ stage of life and health;
  • interpersonal chemistry or rivalry;
  • changes in team members’ salaries or position;
  • ‘near’ factors like the closure of a favourite neighbourhood gathering spot;
  • the health of the wider economy;
  • government policy;
  • levels of outside interest and flows of money into or out of your sector

In short, your organisation is a complex adaptive system within the complex adaptive system of the economy and the world as a whole.

Unlike complicated problems, complex problems cannot be solved, only managed. They cannot be controlled, only nudged. This is the domain of the butterfly effect, where a small change can lead to something big, and a big change can barely make a dent. 

Aaron Dignan

Fruitful thinking

What this means is that trying to eliminate uncertainty or narrowly control outcomes is likely to be futile. Instead you need to ask which nudges will make your system more likely to produce good outcomes. You can think of projects and things you do as seeds with a chance of bearing fruit, and so widely – and position yourself to take advantage of opportunities that crop up in surprising places but seem to strengthen the system.

And as you think about the wider ecosystem and realise that you’re scarily dependent on ‘exogenous’ factors way beyond your control, you can think about how to nurture and protect the flows that you depend on, like flows of information or resources (including people and ideas) into and out of your organisation. How might building a network (for example) strengthen these flows, or tweak the system’s disposition in a way that’s in your favour?

*If you go deeper there are compelling arguments that even our machines are part of a living ecology – see Kevin Kelly‘s What Technology Wants and The Techium for jumping off point into this way of thinking