 In this module, we'll be looking at the process of emergence that is one of the central concepts in systems theory. We'll firstly define what we mean when we use this term. We'll talk about how it gives rise to what are called integrative levels and multi-tiered systems that have distinct irreducible levels to them. We'll look at how this process of emergence can lead to macroscale fractal patterns of organization as a complex dynamic between bottom-up self-organization and top-down coordination develops. The main learning objective to this module will be to understand how emergence creates a macroscale multi-tiered architecture to our engineered environment. Emergence is a process whereby larger entities or patterns of organization arise through synergistic interactions among smaller or simpler entities that themselves do not exhibit such properties, and thus emergent properties are those that belong to the whole system. They only arise when all the parts are put together in a particular manner. The functionality of a system of technology that has any degree of complexity is in many ways an emergent property. It's only when we put all the parts to our car together that we get the functionality of a vehicle of transportation. And many properties to the car such as safety, security and reliability are emergent properties, meaning we have to wait until the car is fully assembled before we can start to do testing on it. There is no point in taking the car for a test drive when it is half-built because the functionality that we wish to test has not emerged yet. These emergent properties can't be studied by physically decomposing a system and looking at the parts in isolation, what is called reductionism. They can, however, be studied by looking at each of the parts in the context of the system as a whole. A microprocessor can only be properly understood by looking at its function within the whole computer system that it is a part of. Emergent properties are the product of the interaction between the components within a system and typically cannot be deduced by reference to the properties of the parts. Thus, emergence typically produces a novel phenomena that we could not have predicted until we ran the system and all the parts have interacted. An example of this might be our concerns around technologies like genetic engineering or algorithmic trading. We can fully analyse and understand how an individual trading algorithm behaves or what effect altering the genes in a plant has on the plant in isolation. But because ecosystems and financial markets are complex systems where the behaviour of the whole system is an emergent product of these interactions we do not know what emergent behaviour will arise from having many different algorithms interacting or different genetically modified plants co-evolving within a whole ecosystem. The net result is an emergent phenomena and we cannot deduce it from analysing the parts in isolation. As a side note, we'll just mention that emergence leads to one of the key concepts within complexity theory that is the concept of uncertainty. The fact that the future emerges is a key source to the fundamental uncertainty within complex systems. If we take something like the internet we don't know what future technologies will be built on the network or more importantly how these technologies will combine to form new possibilities. In this world of complexity the future is not just unknown, it may well be in fact unknowable and this fundamental uncertainty changes our whole approach to the future. This is a little bit outside of our discussion here so we'll move on for the moment. Emergence gives rise to new levels of organisation, what are called integrative levels. The theory of integrative levels describes how new levels of organisation emerge out of lower levels of complexity. To understand the relevance of this to technology we might think about how we needed to have the agricultural revolution before we could have the industrial revolution and in turn needed to have both of these before we could have the information revolution. A mobile phone without any farms to feed us would be pretty useless. The terms platform technology or multi-tier architecture are used to capture how technology systems are built on top of and enabled by other technologies. A functioning urban centre that provides a high quality of life to its citizens is an emergent property of multiple layers of technological infrastructure. Each layer needs to be properly integrated to enable the technologies it supports. Although emergent properties can arise without self-organisation, as in our former example of the car, emergence is also a product of self-organisation. With self-organisation individual components interact, synchronise to form patterns and out of this emerges a new level of organisation. This process of emergence doesn't just stop at one level. Elements interact and self-organise with new levels of organisation emerging but then this new system starts to also interact with other systems in its environment. With the net result being that another level emerges. The parts in our car give rise to the global functionality of the car but then this car is put into operation within a transportation system and interacts with other cars as we get the emergence of traffic. Whereas the car was produced through a formal design process, traffic emerges through the self-organisation of all the individual cars interacting. Thus, through this process of emergence, we get the development of a multi-tier system. This multi-tier hierarchical structure can be seen in the formation of urban centres. From the perspective of technology analysis, urban networks are really the fabric of our engineered environment on the macro scale. They are dense concentrations of integrated infrastructure, technology and services that have emerged over a long process of evolution and they have a hierarchical structure to them from villages to towns to cities to metropolitan areas. This hierarchy is described in the central place theory, a geographical theory that seeks to explain the number, size and distribution of urban centres. It describes how certain differentiated services emerge at a certain threshold to scale. A village can provide some set of basic services. With a collection of villages, we can get the emergence of a town that will provide certain differentiated services in its functioning as a regional hub. And again, with a dense enough concentration of towns, we will get the emergence of a city and so on all the way up until we get globally differentiated metropolitan areas where one can access certain advanced services that are not available anywhere else. As would be the case with global cities like New York, London or Tokyo. This is an example of an emergent multi-tier system through distributed self-organisation, no one's designing this urban network. As we go up this hierarchy through different tiers, the economic infrastructure fundamentally changes from serving the function of primary production to manufacturing to services, information and knowledge activities. This is the three sector hypothesis to the development of economic infrastructure and it is the macro scale structure to our global economy. Each level to this hierarchy allows for greater specialisation and differentiation. A small village serving a few hundred people can only really provide the basic services that the mass of people need. But a global city like Singapore can provide highly specialised financial products because it plays a differentiated role within Southeast Asia and the global economy as a trade and financial hub. As we go up this hierarchy, there will be thresholds and tipping points beyond which we get the emergence of new phenomena. One way to think about tipping points is that many emergent phenomena are discrete meaning either you have them or you don't. Either a city has an airport or it doesn't, you can't have half an airport. But many factors are also continuous, like the population of a city. You don't go from one million people to two million people, there's a long continuum in between. When we combine these two metric systems, because one is changing continuously and the other in a discrete fashion we get tipping points. To illustrate this, imagine the government in a country makes a policy that once a city reaches a threshold of a million people then they'll fund the building of an airport for that city. The result is that the population may be growing at a steady state for many decades or even centuries without any airport. And then just a few more people are added to get a million and we suddenly get a flip within the discrete variable from a city without an airport to one with an airport. And this flip came about through a very small change to the continuous variable. This is a somewhat stylized example, but it helps to illustrate the dynamic behind thresholds and phase transitions. This hierarchical structure that emerges within complex systems often creates patterns that repeat themselves at various scales. What are called fractals? Such as can be seen in seashells, the emergent patterns of a snowflake and the macroscale structure to our engineered environment. The emergent pattern created by the central place theory is a fractal that has this scale invariant property where we find the same network pattern on the micro level of an individual village as on the macroscale of a national urban network. Characteristic of these fractals are power law distributions that describes a power or exponential relationship between the frequency of the occurrence to a phenomena and the scale of that phenomena. Urban networks have been shown to follow this power law relationship between the size of the city and how many cities there are of that size. This is quite remarkable that through a somewhat chaotic self-organizing evolutionary process we get this macroscale pattern of organization that has a quantifiable regularity to it. This fractal structure is a very economical way to create a macroscale pattern through iteration of some simple rule. We get the same structure on the micro level and the macro level that gives the system scale invariance. But this scale invariance doesn't mean that the system is the same on its different levels. It is simply a global structural pattern that emerges within nonlinear systems because of iteration and feedback. Through emergence and phase transitions properties describing one level of a complex system do not necessarily explain another level despite how intrinsically connected the two may be. At each level of complexity new laws, properties and phenomena arise with their own internal dynamics that is specific to that level of organization and can't be reduced to simple aggregates of lower level phenomena. Different functional levels to our economic infrastructure run on very different principles. The primary sector, industrial sector and services sector are all governed by their own internal dynamics and set of rules. Thus supplying an industrial logic to services simply doesn't work. One may emerge out of the other but they're based on fundamentally different rules. With this process of emergence and the creation of a multi-tier system we get a complex dynamic forming between the bottom-up process of organization and the global pattern that has emerged as it feeds back to enable and constrain the components on the local level. Being part of a city and that macro scale pattern of organization both enables us to do more as we are enabled by a vast technology infrastructure giving us access to a wide array of services but it also constrains us as there are global standards and rules that have to be followed in order to coordinate the system on the macro scale. As an example of this we might think about the phenomena of urban gardening in Detroit, USA where due to a mass exodus of people there's a significant amount of unused land within the city and locals have moved in to start small garden farms on these open spaces. This is a bottom-up self-organizing process where people are simply reacting to local phenomena but it is in strong tension with the macro scale pattern of organization as an industrial city like Detroit plays a differentiated role within a region as the manufacturing, commercial, residential and economic hub. The macro scale pattern of organization that has emerged is not designed to accommodate this local self-organizing phenomena. Because of the irreducible nature to emergence this tension between bottom-up and top-down organization is a fundamental phenomena within complex multi-tiered systems and trying to resolve it is a key design engineering challenge. In this video we've been talking about the process of emergence how novel properties to whole systems emerge through the interaction of their parts that cannot be deduced by analyzing the parts in isolation and how this process of emergence gives rise to new levels of organization called integrative levels with the formation of multi-tiered systems. We looked at how this process involves differentiation, tipping points and may result in the formation of fractals as structural patterns repeat themselves on various scales. Finally we discussed the irreducible nature to emergence and the complex dynamic between bottom-up and top-down forms of organization that is an inherent part of these complex engineered systems. Thank you.