The “Brisbane Club” model: mind, society, economy as complex evolving networks
What differentiates our contribution to the study of the Fourth Industrial Revolution from others is the mode of analysis it applies. We make use of a model of the economy which was specifically designed to account for the effects technology has at all levels of analysis: from the micro-scale of everyday life to the macro-scale of the socioeconomic system as a whole. With this model we can “place” the various mega-technologies of the Fourth Industrial Revolution within it and then project their likely interaction with the broader socioeconomic system.
This model was developed in the early twenty-first century at the University of Queensland through the contributions of Jason Potts. Kurt Dopfer, John Foster, and Stan Metcalfe as well as Ulrich Witt and Peter Earl in particular, hence it is known as the “Brisbane Club” model. This model conceives of the economy as a complex evolving system formed by individuals acting on the basis of their socioeconomic environment and psychology, enabled by the technologies available to them. It incorporates elements of behavioural and psychological economics (Earl, 1983, 1984, 1986, 2017), institutional economics where it focusses on the rules governing socioeconomic interaction (Dopfer, Foster and Potts, 2004; Dopfer and Potts, 2008), and evolutionary economics (Metcalfe, 1998; Witt, 2008). It is also strongly influenced by the literature on complex systems and emergence within them (Potts. 2000; Foster. 2005; Foster and Metcalfe, 2012).
We will introduce the Brisbane Club model of socioeconomic systems at some length so that we may apply it in later chapters to analysing the mega-technologies of the Fourth Industrial Revolution. We will first introduce the argument that we can best understand socioeconomic evolution as a process of structural evolution in the formation of socioeconomic networks. We will then introduce the Brisbane Club model of how those networks form out of the interaction between individual psychologies and the socioeconomic environment, and then discuss the various factors influencing the evolution of those networks through the change of individual behaviour. We will then introduce the micro-meso-macro perspective by which we switch between microscopic and macroscopic analysis of socioeconomic systems. We will finally summarise how we will use this model to analyse the various mega-technologies of the Fourth Industrial Revolution. For the interested reader, a technical appendix contains a sketch of the formal properties of this model.
Society and economy as complex evolving networks
The core proposition around which the Brisbane Club model of socioeconomic systems is built is that the economy is a complex evolving system formed by individuals acting on the basis of their psychology and socioeconomic environment enabled by technology. These systems are appropriately thought of as network structures where individuals form connections whenever they decide to transfer or exchange goods and services, mediums of exchange, or information. Anytime you interact with someone in a socioeconomic context, you form a connection in socioeconomic networks. Buy a cup of cotfee, a connection comes into existence between you and the vendor. Exchange your labour for wages, a connection comes into existence between you and your employer. Strike a multi-million-dollar investment contract with another company, a connection comes into existence between yourself and your counterpart in that company.
That of course sounds like a natural way to model socioeconomic systems, but for various historical reasons, traditional economics is not “done” in this way. The tendency for economic analysis (as Philip Mirowski argued in 1989) is to imagine that the economy is something like an electromagnetic field, which is a complete network (all connections that can be made are made) where socioeconomic interactions are akin to electromagnetic flows settling down to an equilibrium. This perspective was immensely useful for understanding the interaction of price dynamics across many markets — changes in one market leading to changes in another and so on. The problem with it, however, as Jason Potts argued in his seminal New Evolutionary Microeconomics (2000) was that it is difficult to make sense of structural evolution with such a model. If a system is fully connected there aren’t any new connections to be made. The alternative Potts offered was to recognise that the network structure of the economy is incomplete and therefore interesting: new connections can be made, existing connections can be transferred, and the structure of the economy can evolve.
Potts’s argument was to stimulate a decade of thought at the University of Queensland under the leadership of Professor John Foster at the School of Economics. Various thinkers from across the world concentrated on the School, becoming the “Brisbane Club,” and contributed elements to the view offered by its emerging model. This model integrated insights from psychological, institutional, and evolutionary economics, while keeping traditional analysis as a special case. To analyse the mega-technologies of the Fourth Industrial Revolution we will make use of the model as synthesised and formalised in two technical documents written by one of the present authors over the course of his doctoral research (Markey-Towler, 2016, 2018a).
New technologies manifest in this model by their effect on human behaviour and the way they thus cause socioeconomic systems to evolve in a structural manner. So, in order to prepare ourselves to apply the Brisbane Club model to analysing the mega-technologies of the Fourth Industrial Revolution, we need first to understand how socioeconomic systems emerge from human behaviour, how human behaviour is determined, and how human behaviour evolves so as to cause the system to evolve. We can then analyse the effects of the mega-technologies by considering their nature and how that nature interacts with human action to cause behaviour and socioeconomic systems to evolve.
