Moving beyond “smart cities”by Alan Wilson / April 21, 2016 / Leave a comment
More than half of the world’s population now lives in cities. In the developed world, many cities which were seen as being in relative decline—such as London in the 70s—are now driving national economies. The quality of life and ongoing economic development now depend on cities being successful. It is important, therefore, to understand cities and use our knowledge to support them.
A city is a system made up of interdependent elements: population, housing, employment and access to services, including utilities, education and health, and transport. Cities are part of a national system connected through air, road and high-speed rail, which is critical to national well-being. This national system is in turn is a subsystem of a global system.
What do we know? There is an embryonic science through which we
know quite a lot. Possibly as importantly, we also have a good idea of what we don’t know. Much of our knowledge is parcelled into disciplines and one challenge is to draw this together and to integrate it. In all cases, our knowledge is partial. Demographers, for example, have good theoretical models of population change. However, these depend on assumptions about birth, death and migration rates. The first two follow historical time trends pretty well, but the third is very difficult and throws considerable uncertainty on forecasts. We have knowledge at different scales. Sociologists can focus on how individuals and families live in cities. Economists are typically micro or macro focused and yet much of the interest in urban economics can be seen as in between—a meso scale. Geographers fill this gap to some extent. We need the knowledge of engineers on how infrastructure functions and how to articulate the challenges and opportunities both present and future, especially in relation to technological change. In some cases, we have accurate computer models, of transport flows for example; and most large retailers would now use these kinds of model to optimise their networks.
“Design is about inventing possible solutions to problems and meeting challenges-about generating policies and plans and incorporating these into scenarios”
This kind of analysis tells us how cities work and provides a basis for articulating the challenges, present and future. What it doesn’t do is tell us how to meet challenges. We then add two key concepts: policy and design. Policy is about formulating objectives and problem solving. Design is about inventing possible solutions to problems and meeting challenges—about generating policies and plans and incorporating these into scenarios. At this point, we have come full circle: the analysts can evaluate the scenarios. This can be done formally through cost-benefit analysis and the analysis can provide the basis of public debate and the political decisions that follow.
Those of us working in urban science have an advantage in that the results of basic research can be applied quickly. If we focus on the challenges, we can both apply what we know, and target an ongoing research programme. At present, smart city initiatives are the focus of much analysis and research. For the longer term, there are major challenges that demand radical thinking: meeting the demands of a growing, ageing population; responding to acute social disparities; providing an effective education system; providing the skills to support a successful economy; meeting low carbon and other sustainability targets; reinvigorating the planning system; and reorienting transport investment to support the local as well as the national.
To bring about these changes, we must move beyond the fashionable mantras of “big data” and “smart cities.”
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