From computer software and trading systems to urban infrastructure and kitchen appliances, processes that govern our daily life have become increasingly interconnected therefore increasingly complex. Millions upon millions of codes, algorithms, artificial intelligence sprawl throughout our everyday devices, thus limiting our understanding. However, having a detailed comprehension of the line of code or the succession of calculations a specific software has been created from does not appear as an absolute necessity for the everyday person. Understanding our car software is not a prerequisite to be safely transported from a place to another, but what is more disturbing, argues Samuel Arbesman in his latest book Overcomplicated is that experts or even scientists who build these systems can no longer understand their complexity.
The conventional wisdom that suggests that “if we work hard enough” we are able to master or understand everything around us, and even more so for the things we have conceived, has become more and more challenged. We “can master all things by calculation” wrote Max Weber, but this positive representation of science is no longer viable, according to Arbesman. We have entered an “overcomplicated” era: “more and more we are building new things that we can’t fully understand, they are simply too complex”.
To be complex a system must not only be the sum of lots of different parts but these parts must be connected between themselves and interact in various ways. When this happens, Arbesman explains, “there is some specific behaviour, small changes, cascades, feedback occur in complex systems. These characteristics take systems from complicated to complex”. Ideally, these systems are built with a great level of resilience with features that help dealing with disruptive behaviours or feedback. Yet, sometimes when the system is corrupted or defective, the level of intricacy between parts is so complex that the logic behind it escapes human comprehension.
This would be an interesting theory that could lead to further debate on whether or not the human brain is truly ill-suited to understand complex systems, but some rather tragic stories illustrate the sheer scale of the problem. The inability of the Toyota engineers to understand the cause of the ‘unintended acceleration’ of the car engine that led to several fatal accidents is a compelling example. Thus, given that bugs are everywhere and they can’t be all eradicated, Arbesman questions the attitude to adopt towards complexity.
With constantly evolving systems that are more and more difficult to understand in their entirety, Arbesman suggests we should embrace diversity as well as complexity and accept a certain “messiness to the world”. This requires a “biological thinking”, in other words an incremental or holistic approach. This sentiment is echoed elsewhere, not least with regards to the circular economy. It is interesting to note that in recent decades this systems thinking approach has gone beyond computer sciences, physics or biology and found applications into social sciences or even economics.
The circular economy framework encourages us to consider the economy not as a deterministic, closed system but one that is indeed complex and dynamic. With this understanding comes a different approach. Rather than trying to predict and control what happens next, it’s the ability to discern patterns, relationships, and considering the system in constant renewal that will be the new guidelines for prosperity. According to Arbesman, we’ll need to adopt this “humble approach” to make sense of the modern world. We need to learn to feel at ease with feedback and uncertainty, and adopt resilience and evolution as the new goals.
Book Details: Overcomplicated. Technology at the limits of comprehension, Samuel Arbesman, Current ©2016
Lead image: © dja65 / stock.adobe.com