With the rise of the internet, we are starting to build new forms of networked organizations and economies. What I want to argue in this post is that these new kinds of organizations are best understood as complex systems and that we need a start to use models from complexity science in the design of these organizations if we are to realize successful and sustainable outcomes in this transition towards a decentralized world.
I want to firstly give a quick overview of complexity science before talking about how it will help us in building these emerging forms of networked economies. Complexity theory is a new approach to science that studies large distributed networks – what are called complex systems. examples include ecosystems, financial markets, the internet, or social networks. Without centralized coordination, organization emerges out of distributed interaction in processes of self-organization – as seen with the flocking of birds or the formation of traffic jams.
In its most basic form, complexity theory can be understood as a set of models that are used to understand and analyze complex systems. But first, let’s just refresh our memory as to what a complex system is? A complex system is a special class of system that has the characteristics of complexity. Complexity means that it has many parts, that are autonomous, highly interconnected and interdependent.
Probably the most important feature to complex systems is this idea of emergence. The fact that when we put things together they start to have new combined macro-level properties and patterns that none of the parts have separately. There are many examples of this, consciousness is one good example, the brain is made up of these very basic operating units of neurons, but when we combine billions of them into networks we can create awareness, consciousness and what we experience as reality. Self-organization. Without centralized coordination and with a degree of autonomy comes the capacity for elements to self-organize. They can synchronize their states or cooperate, resulting in the emergence of patterns of organization from the bottom-up.
Nonlinearity is another feature of all complex systems, very closely related to emergence. Nonlinearity describes how when we put two or more things together their effects may be more or less than a simple summation of their effects in isolation due to synergies between the parts. It also relates to this same phenomenon over time where feedback loops work to amplify or dampen down effects to give us super- or sub-linear change, meaning small causes can have big effects over time or vise versa.
Network structure. Because complex systems are highly interconnected these connections come to form a network structure and it is really the makeup of that network that comes to define how the system works rather than the properties of individual parts themselves. As the famous sociologist Manuel Castells puts it “the logic of the network is more powerful than the powers of the network.”
Without centralized coordination, complex systems develop on the macro-level through a process of evolution. Elements within complex adaptive systems are subject to the evolutionary force of selection, where those that are best suited to that environment are selected and replicated while others are not. Products are subject to selection within a market environment. In democracies, politicians are subject to selection by voters, and creatures in ecosystems are subject to natural selection through competition. You might ask why do we need a new science dedicated to studying complexity? It turns out that systems that are complex behave very differently from those that are simpler in nature, and much of our traditional tools of science are not really designed to deal with complexity.
So why is any of this important? It is important because our economies and organizations are changing and they are starting to look more like these complex networks every day. As a consequence of globalization and information technology, the world has got a lot more complex in just the past couple of decades, and in many ways, our traditional industrial age systems of organization are stalling and starting to fail in the face of that connectivity and complexity; social media disrupting politics; the flow of migrants across borders; the traditional enterprise hierarchy is being transformed; national economies have become connected into a global logistics network; financial systems are becoming destabilized through global interconnectivity.
Our existing centralized closed organizations are not designed to deal with this level of hyperconnectivity. Really we need new forms of networked institutions if we are to harness this connectivity towards solving these wicked problems. The emerging decentralized web and new forms of decentralized economies give us the tools to transform the centralized systems of today into the decentralized networks of tomorrow. It is now apparent that we can take any of our systems of organization – from energy, to finance, to water, food, education or security – and we can convert them into a decentralized network based upon blockchain tech and token economies. Doing that gives us the capacity to harness the resources and incentives of the many instead of being always dependent upon the few within the centralized organization.
It is that quantum leap in approach that we need to tackle the major issues of today because governments aren’t going to solve climate change or corporations going to solve inequality. If we want to solve those kinds of problems we need to design and build networks that incentivize people in the right way in how they interact locally so as to lead to the emergence of global desirable outcomes – linear cause and effect kinds of centralized institutions are of little help when it comes to very complex issues.
Misalignment of Incentives
Today because of the nature of our economies, we are incentivized to take actions that have negative externalities for the environment and society. We are incentivized to over consume and then we leave it up to governments to try and solve all the problems this creates, which leads to really inefficient and sometimes ineffective outcomes. When what we really need is to design networked economies based upon simple rules that incentivize us to act in ways that create positive externalities and lead to the emergence of beneficial overall outcomes.
With the use of tokens this is now possible, we can begin to incentivize the actors in these networks toward actions that have positive externalities leading to emergence. So at the moment companies are incentivized to sell us lots of plastic products that then break, we throw them away, the emergent outcome is mass plastic pollution, that we then have to create government regulation to come and clean up, hugely inefficient really. But imagine if you could directly incentivize companies not to create all the waste in the first place, that would be radically more efficient. This same principle applies to pretty much everything, for healthy eating for example, for incentivizing towards informative and educational content over endless entertainment – and we might think, what would be the emergent outcome if we were all better educated and informed when it comes to politics?
The reason we have not done this is because it is complex, it is much simpler to try and impose a centralized order on the system than designing these decentralized systems that lead to beneficial emergent outcomes. However, this is really what we are challenged with doing today and token economies are really the means through which we can do this.
The key challenge now is in designing these decentralized networks but the truth is we are not very good at it, simply because we have very little experience in this realm. The important thing to note here is this idea of centralized versus decentralized systems. This is the most important thing because as you go from centralized to decentralized you are basically going from a system that is governed by the rules dynamics and mathematics of simple systems to these decentralized systems that are best understood and designed with the models of complexity theory.
This is really two very different worlds. Centralized systems that we know so well which are modeled in terms of simple linear systems and these new forms of decentralized systems that are not; they are nonlinear complex systems and if we are going to get serious about designing and building them we are going to have to bring these models from complexity theory to bear.
A better understanding of this big idea of emergence in design is key. This is because with decentralized systems we can’t control the network directly and specify the outcomes we can simply create the context and initial conditions that will incentivize the actors towards the desired emergent overall outcome. Understanding emergence means figuring out the dynamics of self-organization, how local interactions, can reinforce each other through feedback to create attractors and the emergence of organization.
We need likewise to understand the feedback loops in the system, positive feedback that drives exponential change or negative feedback that dampens it down. This is exactly what rating and review feedback systems do, they are like little signals left behind by users that indicate to others to do more or less of that action. Out of this emerges a ranking system and some kind of order that is not fixed or imposed top-down but emerges from the bottom-up, constantly being created and recreated through local interactions.
We have to understand the structure of the networks in these economies. There is a whole science of networks that can be of great use here to help us understand how what happens in the system is a function of the structure of the network. The dynamics of evolution are obviously very important, prediction markets are a good example of this. Prediction markets are exchange-traded markets created for the purpose of trading the outcome of events, they help us to bring in the dispersed information of the many and define the best options to select based upon that information. From this we get decentralized decision making based upon the information and knowledge of the many who have skin in the game.
I think we are in a technological revolution that can be compared only to the advent of agriculture or industrial technologies. It is difficult for us to try and conceive of how radically those revolutions changed our society and us as humans – but I think today we should be open to such unimaginable transformational change when thinking about the future. I think the two most important technologies of our time are data analytics and blockchain networks. They are such powerful technologies because they don’t just shape the world around us they both shape how decisions are made and we organize ourselves.
We have a lot of issues on the global level that we are not able to currently deal with, we really need to use these technologies to enable new forms of networked organizations that are better designed to respond to the kind of complexity the environment is presenting us. When designed properly these large scale decentralized systems could have the potential for the kind of powerful emergence that is of the magnitude and capacities required. However, I think to be successful in building this decentralized world in a sustainable way we are going to have to start to think differently, using these ideas of complexity theory.