 Complex systems are, by many definitions, highly interconnected, examples being social networks, financial networks, and transportation networks. In these highly interconnected systems, it is increasingly the connections that define the system as opposed to the properties of their constituent components. This is quite an abstract concept, so some examples might help us to grasp it. Think of the expression, it is not what you know, but who you know. It would be more accurate to say, in an isolation system, it is what you know that matters, but in an interconnected system, it is increasingly who you know that matters, that is, the connections that you have. Another more concrete example might help to illustrate this important concept better. Think of an expensive sports car. Out on the highway, it is king, doing 0-60 in under 3 seconds and up to 250 km an hour. These properties of the car are admittedly pretty cool, but put this car in urban traffic and it will be gridlocked like any other car. No matter how great the properties of the car, it will only be going as fast as the transportation network allows it. This should demonstrate that in these complex systems, it is the structure and dynamics of the network that really matter. It's not about being bigger, faster or stronger, it's about access and access is defined by where you lie in the network and the structure of that network. Think of the air transportation system. It is not so much the static properties of your location in space and how far your destination is, but more importantly where you are located in the network. If you are beside a major hub, it can be quicker and easier to travel to another major hub on the other side of the planet, as it would be to travel from one disconnected hub to another that is a fraction of the distance away. So hopefully these examples illustrate to you the importance of seeing these complex engineered systems from the perspective of connectivity and networks as opposed to seeing them as things, irrespective of whether we explicitly call them networks or just systems, networks are the true geometry behind complex systems and thus it is very important to think about designing them from this perspective of access, connectivity and network structure. In order to do this, we first need to understand a bit about the nature of networks. And network theory is an area of math and science that provides us with the models for analyzing networks. So let's take a look at some of the key features to networks and how they will affect the system as a whole. Probably the most important feature to a network is its degree of connectivity, that is, how connected is the whole system? Designing for a densely populated urban environment like Hong Kong will be very different to designing for a city like Los Angeles which is dispersed. In highly interconnected systems, the dense interconnections can require much greater layering. The components can be much more specialized and there may be a much higher level of dependencies. As a result of this, failures can quickly propagate. A small security scare in one airport, for example, can result in delays across large areas of the air transportation system within a nation. In these large, highly interconnected systems, we don't always know the dependencies. No one has complete knowledge of all the interlinkages that regulate complex systems like large urban centers or our global supply chain. Thus our aim should not be to design these systems to be perfect, 100% fault tolerant. This is not realistic. Instead, they need to be engineered so as to be robust to failure. The internet again is a good example of this. It is what is called a best effort network. This means it tries its best, but if something goes wrong, then it is no big problem. It just drops your packet and tries again. It happens all the time, but the internet still works. The occurrence of failure should be designed into these systems and not out of them in order to achieve robustness. Another key consideration in the design of these networked systems is their degree of centralization versus decentralization, as this is a defining factor in the structure and makeup to networks. In centralized networks, we have a node or small set of nodes that have a strong influence on the system, and the network will be largely defined by the properties of these primary nodes. These centralized networks can leverage economics of scale and it is possible to have a high degree of control over the system through one point of access. Due to this, centralized networks can be very efficient in the short run, faster and easier to manage, but they are also more vulnerable to strategic attack, often less robust and sustainable due to their dependencies upon a few centralized nodes. They can also result in a high degree of inequality and problems in load balancing. This is due to the occurrence of highly centralized peak demands for resources, with rush hour traffic jams and exaggerated properties prices in the center of cities being an example of this. The heavy use of economics of scale engineered in industrial systems of organization means many of the networks that make up advanced economies are highly centralized, including our global financial system, centralized around a few key nodes, many national transportation systems and logistics networks which are designed as centralized hub and spoke structures. Decentralized networks are in contrary without centralized nodes, responsibility, control and resources lie on the local level and are dispersed amongst a large percentage of the nodes. Examples of these include peer-to-peer file sharing, sustainable agriculture systems, car sharing services and direct democracy. Decentralized networks typically require greater user engagement as they cannot depend on centralized batch processing and economics of scale. The nodes in the network are often more self-sufficient and less specialized and thus easier to interchange and replace any node with any other, making them less susceptible to attack and more robust to fail. They also have less dependencies and are typically more sustainable in the long run. In this section we have talked about the importance of seeing complex engineered systems as networks and how the different structures to these networks has a significant effect on the overall dynamics of the system. Thus whether we are designing a health care service, a logistics network or a new financial service, having a visual representation of the system as a network and being aware of how our interventions will alter this structure will be of great value to us.