On 21 January I was invited to give a lecture at the Master in Smart Cities and Sustainability of the Complutense University (UCM) on how data and processes can help to design a public space that improves both the urban experience and the climate footprint of cities as a whole.
The urban problem
Before the Big Data boom, urban planner Jaime Lerner, former mayor of Curitiba, said that cities were not a problem, but the solution. A few years after this statement, I decided to do a small test, combining three dimensions: GDP per capita, CO2 emissions per capita, and ‘urbanisation rate’. This is what I got:
Prosperidad y sostenibilidad vs. Tasa de urbanización
What does this graph mean? It means that as countries become more urbanised, overall individual wealth (GDP per capita) increases, but – and this is the really interesting part – emissions per individual also decrease.
In other words, cities make us both wealthier and more sustainable. But why?
The ‘network effect’ and negative allometry
The main reason for the increase in urban wealth is what is known in economics as the ‘network effect’ and in telecommunications as Mercalfe’s Law. This property, which we explained in more detail in a previous post, is basically the rule that drives the Internet economy and is formulated as follows V = K * N2, where V is value (or wealth), K is a constant and N is the number of nodes – in the case of the city, people, since a city is first and foremost a huge social network.
And the property that regulates the reduction of emissions is the same that causes organisms to have a proportionally lower metabolism as they increase in size, and also to consume proportionally fewer resources and consequently produce less waste (always proportionally to their increase in size, mind you). This is known as negative allometry.
(For the reader who wants to know more, we recommend this great book on mathematics and urbanism).
The role of urban design
One might ask, then, what is the point of intervening in cities if they are themselves a formidable invention. If, after all, this ‘organicity’ in urbanism works in the right sense. Or, in the words of the Spanish poet Juan Ramón Jiménez: ‘Don’t touch it, that’s the way the rose is’.
On the face of it, the argument is compelling. But it ignores the constant ‘K’ in Metcalfe’s equation and the allometric coefficient ‘A’ in the case of the second property. This is where urban design can achieve more robust connections between people (increasing ‘K’) and more sustainable cities (decreasing ‘A’).
How? By focusing on the consideration we talked about at the beginning: the city is above all a social network. In it, as the quadratic effect of Metcalf’s Law shows, the whole is much more than the sum of its parts.
In decision theory, there are two types of individual behaviour: the human, which is driven by emotion, and the economic, which seeks to maximise profit in the face of any dilemma. Both types of behaviour are symbolised by two stereotypes of people: humans and econs. Reality is probably more complex. We are neither 100% econs nor 100% humans, or alternatively one or the other, depending on the purpose.
The city, its public space, its physical infrastructures, such as mobility, or its digital services, are also designed by humans and econs, who are not always humans and econs either, and are both to varying degrees. Urbanism and urban design thus become, in the words of Charles Landry, a mixture of art and science that feeds several disciplines. One of these, which has recently been incorporated into the urban sciences, is psychology.
Boston transit. Real vs perceived distance. Source: City Form Lab
As can be seen in the figure, when designing the Boston tram stops to reach a certain percentage of the population, it is not the same to consider the Euclidean (real) distance as the perceived distance. If the person taking the tram perceives that his or her home is more than a certain distance away – humans normally work with temporal distances – he or she is very likely to abandon the tram to move around the city. And if the calculations for positioning stops and lines do not take into account factors such as slope, road hazards, lighting, pavement condition or width, we will miss the mark.
Data, processes and organic public space In order to design cities that are better adapted to the people who live in them, it is necessary to better understand how the urban environment affects us. Digital and public space usage data needs to be part of the urban design toolbox, which also needs to become more agile and iterative. This agility and iterativity is what we call ‘evolutionary urban design’, adapted to the complexity of urban ecosystems such as the shopping street illustrated in this article.
Brasilia: diseño urbano top-down vs. bottom-up
Urban design by ecologists, as symbolised by the modern movement and of which Brasilia is a paradigmatic example, may have made sense at the time. But the photograph shows the conflict between urban design and human desire. The seemingly anarchic ‘lines of desire’ in the grass between the symmetrical branches of asphalt set the tone for future urban design.
Digital public space is not public
Today there is an abundance of data generated by our digital footprint, and the evolutionary methods already used in the production of digital services are well known.
Desire ines in New York City’s Central Park. Data and visualization by Nike
All this data, together with the sensors that collect it and its representation, as in the photograph, configure a new digital public space that needs to be reinvented and redesigned with human needs in mind. However, two problems stand in the way: the privatisation of data and design processes that do not use iterative methods.
Unless urban design can make urban data available as a public good, as raw material for the agile design of digital public space, smart cities will remain essentially anchored in the modern movement.
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