Words by Poornima Paidipaty
Historian Poornima Paidipaty explains how new data streams could give a more nuanced picture of how cities work, and why they fail
The Possible: How do we change cities by measuring them?
PP: Measuring the social world is not like measuring something like a table, where nothing much will change as a result. It changes how we see it, based on what we decide to focus on, how we decide to present that information, what we think that information means. It wasn’t until the 20th century that we started to measure inequality in terms of income. In the 19th century, it largely meant political inequality, but once we produced the data to look at income, economics became much more dominant. Over time we have come to see the economy as central to whether a society is succeeding or failing. But we can miss out on all kinds of other ways of thinking about what makes an equitable society — issues of gender, race, caste or ethnicity. Then there are quality of life aspects, like how long it takes to commute to work or how long you sit in traffic exposed to toxic air. Those things get missed entirely by economic measures.
TP: What could these urban metrics help to tell us?
PP: I think we can use them as a way of complicating the picture, to show us what it means to experience disparity, to be at the bottom rung of rising global inequality. Air quality, for example, has extraordinary health consequences. The quality of air in India, in internal cities especially, is very, very poor. Wealthier residents get to live in spaces where they can be some distance from the city traffic. They might be wealthy enough to run air filters or air conditioners. But people who live close to the streets, in informal settings and slums, or who work as traffic policeman or have shops that are right on the road, have constant exposure. So you can live in the same space, you might have a decent income in the sense that you might be a city worker who has a salary and a pension, and yet you might be exposed to toxins that affect your life and the lives of your children in really complicated ways. We can now measure some of these things.
TP: How this does come into play in urban planning and development?
PP: The rise of big data and very complicated new metrics can give us a very nuanced picture of, for instance, growth or sprawl. Earlier what was measured was really the built environment, the fixed structures and their relationships to each other. Whereas increasingly, we can see not just what exists in a built space but how people interact in real time. What I think is really interesting is that you can take social data and map urban development, whether it’s growth or sprawl or shrinkage, as things that happen simultaneously. We know certain cities are growing and other cities are declining and that seems like a very simple picture. But even within those cities it’s not like every bit of them is growing at the same rate. In New York, for instance, there are certain neighbourhoods that are growing very rapidly and others that are wealthy but less dynamic.
So you can see much more where people are spending money, which public transport corridors are really well trafficked, how people are getting in and out of cities. I used to live in Chicago where the centre looks extraordinarily vibrant in the middle of the day because that’s where people go to work and to shop and to play. And then they go home and the residential neighbourhoods are not the centre of the city. In the last ten years these neighbourhoods have for the first time developed much more dynamic social spaces in terms of galleries or cafes or events in parks. When you notice that people have to go quite far from their homes to find places to socially interact, you can start to see that need.