Which came first, the chicken or the egg? The way this question is phrased implies a linear causality: one exists first, and then gives rise to the other (A → B). We have a tendency to see things this way. We look for root causes, explanations that can be traced back to one person, event, bacteria or machine. If we can find that cause, we can solve problems and make sense of the world. This strategy has worked well for us – we use antibiotics to kill bacteria, we stopped using the chemicals that were thinning the ozone layer, we learn in school that the assassination of Archduke Frans Ferdinand triggered WWI and that the invention of the steam engine led to the industrial revolution.
But we struggle with the chicken and egg problem. Which came first? Neither. Our difficulty in answering the question betrays the game – there is no linear relationship here. It’s more like A ↔ B. The chicken and egg reproductive process is the result of a long evolutionary history, each iteration influenced by the environment and the one that came before. If we take small steps back in time, the difference between each iteration is so small as to be indistinguishable. But take a leap back, and you perceive a difference. At what point in that history of development can we draw a line, when either side of that line will always look basically the same?
We don’t like this kind of problem. It’s harder to think about and it’s harder to solve. If you need experience to get a job, and you need a job to get experience, what should you do? If you need enzymes to make proteins, and enzymes are proteins, how did the first enzyme get made? What about the origin of life?
We have struggled with these questions for centuries. Creation myths and religious explanations are part of every culture, but even they leave us wanting more. My grandfather was a pastor, and he believed that the world was created by God. I asked him once where God came from, and he told me a story.
A pastor was walking on the beach one day, asking himself who or what had created God. He encountered a boy, running back and forth between the ocean and a hole in the sand. The boy was carrying a pail, and filling the hole with water from the sea. “What are you doing?” the pastor asked. “I’m putting the ocean into this hole,” the boy replied. “But the ocean is much too big to fit in that little hole!” he said. And the pastor realised that questioning the origin of God was much the same – too big a question to fit in a human mind.
This is the problem with linear causality. If we search for the one start, cause, origin – there is always something that came first, some earlier start, cause, origin.
Another way of looking at relationships is to see mutual or circular causality. In systems theory this relationship is described using feedback loops. In Buddhism, it’s called Pratītyasamutpāda, or dependent co-arising. Joanna Macy describes the concept well in her book Mutual Causality. My intent here is not to describe mutual causality but to discuss the potential impact of seeing relationships in this way. Using the chicken and egg example, we can say that the chicken and egg came into existence together, co-dependently, each creating the other iteratively over time. We see the relationship between them in a new light, and can then start to ask different questions. To me, this is the core of complex systems theory.
In immunology, the field my research project focuses on, one of the aims of research is to contribute to disease prevention and treatment. Many of the most widespread treatments currently rely on linear causality to identify treatment targets: antibiotics, antivirals, immunosuppressants. But what we experience as disease isn’t just caused by a pathogen in a linear way, it arises from the interaction of our bodies with the pathogen. The same bacteria could make you sick or not depending on where it enters your body, in what quantity, at what time in your life, and with what other microbiota. Whether you experience symptoms of sickness depends on how your body, in the condition of that moment, interacts with that pathogen, as it appears in that moment.
It may seem like adopting this perspective would make it impossible to find solutions, but it actually presents more opportunities for interventions and treatments. Vaccines are the most prevalent example of medical intervention that takes a systemic approach. A vaccine relies on the inherent structure of the immune system and an immune response to perturb the system to a different, desired state. When we get an infection and then experience sickness, the pathogen is perturbing the body (a complex system) in such a way that it experiences a state change, from healthy to ill. A vaccine perturbs the system to a state of immunity from that particular pathogen. There are many potential ways to perturb a system, and those can be exploited for novel treatment pathways. One example is the addition of bacteria to treat unwanted bacterial infections or chronic inflammation (you may have heard of fecal implants being used to treat IBS).
Treatments are certainly getting more creative, and I don’t mean to imply that nobody is finding novel solutions or using systemic methods. However, I think much of the research that goes on (eg finding drug targets) is still based in a conceptual framework of linear causality. The complexity and interconnectedness of biological systems is becoming more apparent as we gather more information, but widespread adoption of a systems perspective has not yet occurred. Innovations like bacteriotherapy arise in part from urgent concerns like increasing antibiotic resistance, and the pressing need to find alternative solutions. I argue that such innovation would be more easily attained if our conceptual frameworks included mutual causality. A post from the blog Emergent Cognition explains it well: “Although one perspective isn’t inherently better or worse than another, each reflects a way of seeing with unique affordances and constraints on how we think.” We can only gain from broadening our perspectives to include circular causality and complex systems thinking.