True Mind Consulting

May 17, 2023

A wicked problem is one that isn’t susceptible to linear thinking¹.


Francisco de Goya — El sueño de la razón produce monstruos

Linear thinking means you frame the problem, you come up with a solution, and the problem disappears. There may be other problems down the line, but you just knock ’em down one at a time and keep going.A trending example is to say we’re emitting too much CO2 by burning fossil fuels, but we still need all that energy, so let’s move to renewables. No more CO2 emissions, problem solved. A slightly more sophisticated version of this says we’ll add in carbon capture and storage (CCS).

This only works within a very narrow mental model or system that only looks at how we generate energy. Start to zoom out at the bigger systems that this is part of, and the neat solution starts to unravel.

The first trap is Jevons’s paradox: making use of a resource more efficient increases rather than decreases the amount used (at least in a system where there are intrinsic drivers for growth such as increasing profit and GDP).


Increase in use of renewables has not led to a decrease in use of fossil fuels

The second trap is that renewables require a massive expansion of mining

… in countries with most existing rainforest, or ocean areas with fragile biodiversity

causing water pollution and violating indigenous rights

… using lots of fossil fuels in the process

… and there isn’t enough of the materials anyway


Palabora copper mine, South Africa with visualisation of actual amount of copper extracted © Dillon Marsh

Wait — how can renewables be worse? Actually I’m not literally saying that and I’m not even sure there is a meaningful single measure you could use for the comparison. But they emphatically don’t solve the problem, while also adding exta difficulties into the mix.

It’s partly because so much of the effect of atmospheric CO2 is already baked in. If all emissions stopped tomorrow, temperatures and sea levels would keep rising probably for hundreds of years.

But it’s also that each course of action changes the boundary of the system we’re dealing with. Just now we were “only” looking at a climate system and its interactions with human society. Now we have to include other elements that change the boundaries of the system. Every system is a mental model that helps us work with things, but anything we do may mean we have to consider new things for inclusion in the model.If we take a step back from the question of energy production and its impacts, we see there are a whole host of interconnected systems with causal links and feedback loops between them.


I came up with this list off the cuff to illustrate the point — it’s not intended to be exhaustive or the only way to look at this.

A couple of things to note:

1.Even without understanding detailed workings of specific processes, we can see broad interactions between factors.

2.Although it’s intuitive to sketch things this way, this goes beyond what can be modelled and simulated using the systems dynamics method based on stocks and flows — we start with natural world phenomena that can in principle be modelled but move quickly into social, economic and political phenomena that can’t as they occur through conscious human agency. If you thought the three body problem in physics was hard… this is orders of magnitude harder.In 1972 a thinktank called the Club of Rome published a report by a group of MIT scientists called Limits to Growth. This used a simplified but rigorous model of world population, technology, resource use and pollution to outline possible future trajectories based on possible policy decisions. It wasn’t a prediction so much as a description of how the world system works. They populated the model with real world data, set parameters for a number of possible scenarios and ran simulations (which was a big deal with the tech available at the time — today you can run them yourself in a browser). The models showed that the Business as Usual scenario — without reduction in resource usage and population — would lead to overshoot and collapse, in other words society would outstrip the ability of the earth to supply resources and absorb waste, leading to a sharp drop in population and welfare among other things.


Simulation result from InsightMaker website (link in paragraph above)

In 2020, researcher Gaya Herrington tested the model based on the 50 years’ worth of data since the book was published, and concluded that we are on track for the “BAU2” scenario which allows for more resource extraction than the original authors had posited, and hence a longer period of growth followed by a collapse driven by pollution (the data were also consistent with the possibility that we can still rapidly innovate our way out of collapse, but other real-world experience makes that look unlikely).


Gaya Herrington’s 2020 update showing fit of real-world data to various trajectories

However, the very fact that the model is still valid 50 years later points to a significant problem — the model was very good at describing the system but not very good in changing it.

Why not? Because although it captured the effects of changing parameters like speed of adoption of environmental measures, it didn’t include a theory of change around how those things would get adopted.

Your ability to affect change is intimately connected to how you look at the system(s) you’re trying to change, of which you are likely to be a part rather than a detached outside observer. There are a number of metaphors for this (and all ways of seeing inherently rely on metaphor, it’s just that most of the time we aren’t aware of it).²


You can see an organisation or society as a machine — this paradigm has been dominant since the nineteenth century and is enshrined in much of management theory. Terms like “tools” or “levers” owe their origins to this way of seeing things, as does any mapping of processes with their inputs and outputs that doesn’t consider people and other non-mechanical factors.


You can see the system as an organism, interacting with an environment and composed of parts that communicate with each other — this is the approach taken by cybernetics, and especially Stafford Beer’s Viable Systems Model. This fills in some of the gaps left by the machine model, but has other gaps of its own as it assumes a single organism that can in principle achieve internal harmony.


A social system can also be seen as a cultural or political construct based around shared rituals and narratives. There are some things that obviously stand out as ritual (the state opening of parliament in the UK is a fun one) but consider also your dev team’s daily stand-up or your quarterly board meeting. This paradigm has the strength of accounting for ways that people actually operate in social structures, but may not account for inequality, hierarchy and coercion.


The existence of these in real life is addressed by another metaphor, that of the social structure, which emphasises tensions between groups of people or between people and the natural world.


The final metaphor I’ll mention is that of the ecosystem or web of interrelationships — this includes modern systems dynamics but also ancient indigenous perspectives.

So am I saying we can do nothing? Not at all. But we have to let go of simple or all-encompassing solutions. Here are three possible guidelines:

  1. Do no harm. In wicked, complex problems any idea of a simple solution is at best hubristic and at worst disastrous. Because there are so many moving and interacting parts, the Precautionary Principle applies. It’s an updated version of the Hippocratic Oath — do nothing that has a chance of doing catastrophic harm. Anything that attempts to change ”the whole system” at once falls into that category.
  2. Find where you are. There is no “view from nowhere”. You are always standing on a particular hill or in a particular valley looking at that part of the terrain that you can see. Every actor who might want to influence the system is also part of the system, which is why there isn’t actually one system that can be objectively defined, there are as many as there are actors, multiplied by the perspectives each actor can take.
  3. Constraints enable creativity. Consider what you know about dependencies, feedback loops and cascading risks as “enabling constraints”. Knowing what you can’t or shouldn’t do is a spur to creativity, just like the rules of any game force you to innovate within the constraints of those rules. In particular, creativity can entail reframing the problem to ask different questions. Knowing that human beings can’t fly by flapping our arms eventually led us to invent flying machines. Knowing that we can’t breathe underwater led us to invent snorkels and SCUBA. To return to the energy dilemma, instead of asking “how can we keep meeting our energy needs without fossil fuels” you can ask “do we really need so much energy?” or even “how can we survive and thrive within the existing energy systems of our planet?” That doesn’t mean you find a magic solution that had eluded you so far — whatever you come up with will have impacts and trade-offs. Using less energy will mean giving up some things we’ve got used to. image
Thinking / perception

The Chinese character³ 想 meaning “thinking” or “perception” consists of a tree — a thing external to you; an eye — your means of becoming aware of it; and your heart/mind — by which you understand it and what you can do in relation to it. You may see the tree as beautiful, and water it. You may see it as shady, and sit under it. You may see it as a source of timber, and cut some or all of it down. The tree is always there, but you’re exercising choice by dint of looking at the tree as opposed to something else, and by dint of the way you look at the tree which in turn shapes the possibilities you see for action.Let’s look at a specific area. I used to work in technology resilience in the private sector, and know people working on the same thing in the health service. Resilience is typically achieved by having redundancy at as many levels as you can afford — servers, data centres, network circuits, network carriers, power supplies. Organisations then supplement this infrastructure-level resilience by ensuring they have robust procedures to deal with unexpected events — also known as crisis management.

Like any approach, it works as longs its underpinning assumptions hold good.

First assumption: there is some level of underlying infrastructure that won’t fail, be that the national power grid, the Internet or something else — the equivalent of a central bank or “lender of last resort” that can prop up failing financial institutions.

Second assumption: the scenarios you can think of are the only ones that can happen.


Illustrative examples of resilient technology architecture


Headline in The Guardian, July 2022

“Whilst the simultaneous failure of both data centres may have been a low probability event, the heatwave (and the potential impact on data centres) was predictable, and yet the Trust risk and governance mechanisms failed to prevent the IT outage of 19th July.” — report into Guy’s and St Thomas’s NHS Trust data centre outage 2022

Third assumption: the point of everything you’re doing is to keep this particular system running, or get it running again if it stops. Walking away from the system is not an option under this assumption.

Applying the three suggested guidelines above could give us something like this:

  1. Doing no harm means not increasing complexity or dependency on energy, water (for cooling) or other resources. The worst thing that happens in technology is that we create more of it to deal with the problems it (or our dependence on it) has caused. More complexity means more things to break and more dependence on people, tools and ultimately energy to fix them. Artificial complexity is the enemy of resilience because it has a finite number of responses to stress and needs to be artificially propped up, consuming ever more energy. Natural complexity on the other hand — in organisms and self-organising social systems — is a friend of resilience because it naturally creates flexible responses that don’t need external input to maintain them, using the energy available.
  2. Find where you are: each actor in the health ecosystem — technologist, health worker, patient — will have different concerns and points of leverage.
  3. Constraints enable creativity: a technologist can build simpler systems that require less energy, or can be accessed offline. A health worker can develop ways of working with patients that are less dependent on technology. Patients, in their extended social settings, can find ways of looking after themselves that draw on the expertise of health workers where necessary while reducing dependence to a minimum by means of social interactions, diet and exercise. In case this sounds naive, 70% of health service usage in the UK is driven by chronic conditions rather than acute conditions and injuries — so even without a climate crisis there is already a need to help people live with conditions rather than imagine they can be fixed.

You may have spotted a paradox here: I started by painting a big picture of a system with lots of interacting parts, but now I’m saying we can’t change the whole system, only some of the parts. In fact the paradox is in reality, and the point of systems thinking and practice is to be able to see it and work with it. It’s not that you can’t change the whole system — it’s just that history shows that attempts to do that in an overarching way always lead to different results than intended. Conversely smaller attempts at change can steer a larger system in a positive direction.


Image credit: JR Forasteros

Embracing the reality of wicked problems, which I’d argue includes all the really challenging issues facing the world as a whole and any organization trying to navigate it, doesn’t mean giving up. Solutions are an addiction, and giving up an addiction is liberating. Seeing clearly means finding ways to look at the world from where you are, and identifying actions that make a difference while avoiding things that make it worse. After each “next right thing” the situation will be changed so you can orient yourself again and see where to go next.¹ This is a simpler framing of a richer topic. Keith Grint distinuishes between simple problems, which can be figured out by domain experts and traditional management techniques; critical problems, which require coercion to get everyone to do what’s needed quickly (like evacuating a burning building), and wicked problems which are largely as I describe them here. A single situation may contain elements of each, with COVID19 a case in point — vaccine development and distribution are simple problems as they follow known procedures; isolation, distancing and mask wearing are critical problems but both the simple and the critical shade over into the wicked problems of a culture where people may not trust their government, governments may have political agendas, people’s exposure and susceptibility to infection are linked to socioeconomic factors which in turn are downplayed by governments and so on.

² My use of these metaphors as gateways to systemic insight and action is taken from Systems Thinking for the Management of Complexity by Michael C. Jackson, who applies the work of Lakoff and Johnson to his own considerable experience of systems interventions.

³ I’m not a Chinese speaker, and apologise to anyone who is if I have misinterpreted any nuances. I was made aware of this character and its implications in an extract from Flowers in the Dark by Sister Dang Nghiem of Plum Village. A couple of days after writing this article I came across a discussion of the same character in chapter 14 of Iain McGilchrist’s The Matter with Things.

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