"When we try to pick out anything by itself, we find it hitched to everything else in the Universe." - John Muir
At first glance, a flu is a straightforward battle between a virus and our immune system, with medicines as our allies.
But when you ask anyone about their experience of the COVID-19 pandemic, they don't just talk about the illness. They talk about what it was like to be stuck at home for several months. They remember what it took to adjust to work from home and rue their cancelled travel plans. They grieve the loved ones they lost, and relive their helplessness. They remember the deluge of changing guidelines and the waves of statistics. They talk about how many boosters they got, and share their opinion on masks. They remember communicating through closed doors in their own homes, and seeing colleagues only in digital windows. They studied to be able to teach their kids, washed vegetables with soap, and wore suits with shorts. They talk about the first thing they did when the lockdowns ended. The most unfortunate ones can't say anything at all.
This was complexity in action. A tiny virus brought our world to its knees, not just by attacking our bodies but by piercing through the delicate and intricate web of our social systems. It was a powerful reminder that in a complex world, small disturbances could have far-reaching, unpredictable consequences.
Our usual approaches to public policy struggled to keep up with this complexity. Even with years of planning and preparation, we found ourselves in uncharted waters, making high-stakes decisions based on incomplete and constantly changing information.
The most important and urgent challenges we face – like pandemics - are not amenable to simple, linear solutions. They emerge from the complex interplay of multiple factors, often spanning domains and scales, and are prone to unexpected shifts and cascading effects.
Policymakers know this. Of course they know this. And they have been trying different approaches to make sense of complex systems for a long time.
In 1972, an international team of researchers at MIT published a groundbreaking study called "The Limits to Growth," commissioned by the Club of Rome. Led by Donella Meadows, they used computer modeling and systems thinking for the first time to examine the complexity of Earth's systems. It was the most consequential analysis of the time, and ultimately, controversial. (We'll dive into this in a future post.)
Today, several systems-thinking tools derived from that approach are used to visualize complexity. A system's boundaries are defined, actors are identified, connections are made, effects are quantified, feedback loops are drawn. These network maps are then analyzed, with varying levels of sophistication, to try and find leverage points for change and anticipate unintended consequences.
By design, these maps sanitize the messy meaning-making by the people and institutions within the system. The focus is on actions and impact, inputs and outputs. The system behaves, even if the people do not. There is comfort and utility in that representation of reality. A map may not be the territory, but it is better than not knowing where you are.
Consider the perspective of policymakers tackling the pandemic using systems-thinking tools. Initially, they would focus on metrics like the volume of travel, infection and transmission rates, testing and hospital capacity, economic indicators, stocks and flows of masks and ventilators. They would highlight the dependence on essential workers and compliance with social distancing guidelines. As new factors emerged – like vaccines – these would be summoned onto our maps, where they would spread out and provoke changes in everything they touched. We mapped, we mobilized, we managed.
We also misread. These maps did not tell the whole story. They did not capture the fear and anxiety people lived in. They did not reflect the trust, or lack thereof, in each other and in governments. They did not prepare us for all the small and large changes we had to make in our lives. They did not account for emergence in an emergency. They could not.
When we subsume the entire human experience of complexity into nodes and numbers, we risk making policy decisions that give the illusion of being technically optimal but are socially unsustainable. We don't appreciate the complex ways that people make sense of, and respond to, change. The dynamic and emergent properties of complex systems elude us. We pursue the knowledge of things that cannot be known and seek control of things that cannot be controlled. Our maps and models which, while temporarily useful, trigger unintended consequences and are brittle in the face of change.
We trade our capacity for imagination for our comfort in illustration.
We need to complement our systems-thinking approaches with additional tools from other domains. At the same time, we need to equip ourselves with a new orientation towards complexity – one which liberates, not constrains.
Niklas Luhmann and Bruno Latour are two thinkers whose approaches achieve both these objectives.
Luhmann's theory of social systems emphasizes the role of communication and meaning in shaping social reality. Each part of society - whether it's the economy, politics, science, or law - works according to its own unique code and logic.
In the context of the COVID-19 pandemic, his approach would reveal how different social systems observed and responded to the crisis according to their own logics, and how these systems interacted and co-evolved over time.
For example, the global financial system's turbulence, including the liquidity crisis in the US Treasury market, was not a direct effect of the virus itself, but the result of the system's own operations as it processed the pandemic according to its code of profit/loss.
Luhmann's approach would explicitly highlight what he calls second-order observation - observing how others observe. Media reports about "pandemic fatigue" or "vaccine hesitancy," for example, represent observations of how others are observing and responding to the pandemic, which in turn, could be incorporated into systems thinking maps to identify new leverage points.
Luhmann's approach would liberate us from the boundaries of the system we are concerned with, and provoke conversations with other unfamiliar systems with their own distinctions and practices.
Bruno Latour's actor-network theory (ANT) focuses on the associations between human and non-human actors. ANT rejects traditional dichotomies between nature and society, subject and object, and instead traces the hybrid networks through which phenomena like the COVID-19 pandemic emerge and evolve.
In the context of the pandemic, an ANT approach would involve following the various actors involved - from viruses and face masks to policymakers and public health communications - and tracing the complex web of specific interactions through which they constructed their pandemic reality. The ANT approach rejects amorphous social forces. 'Culture' or 'pandemic fatigue' would not find a place on an ANT map; we would be forced to translate these explanations into specific actors and their associations. (Who was fatigued? Which specific actor was acting on them? What connected those actors? Were they connected by a transmitting force or a transforming force? How did fatigue manifest itself?)
Latour's approach would liberate us from our tendency to use convenient abstractions - no '-isms' allowed. We would follow the actors as they constructed their experience of their complex world. We would be free from our need for finality, free to embrace the open mood of continuously 'assembling' and 'reassembling' the system.
Meadows, Luhmann and Latour were not primarily concerned with complexity. Each of them brought their own histories and orientations and skills into their ways of making sense of the world. Their approaches reflect their specific concerns and purposes. The diversity of their approaches mirrors the diverse nature of complex challenges. The pandemic was simultaneously a biological phenomenon, a collective meaning- making process, a communication challenge, and an economic problem, all intertwined in a complex network of human and non-human actors.
Why, then, should we limit ourselves to one way of mapping the world?
Ultimately, navigating complexity is not just about hitting certain policy targets or optimizing systems. It is about cultivating our capacity to survive, adapt, and thrive in the face of permanent uncertainty. It is about creating the conditions for people to make sense of their world and empowering them to have a voice in the decisions that affect them.
Each person's pandemic experience was unique, and each gets to tell her own story.
I plan to write a series of posts examining different complexity themes and approaches. Subscribe to join this journey.