NPR on big data, big cities
As an introduction to its piece on big data for big cities this week, NPR delivered one of the more poetic descriptions of big data to date.
Here is an example: "Every function of our culture is generating reams of numbers that flow into the data sphere…hidden in all that information lies a hyper-resolution map of the world's behavior in space and time. It's a representation of human life and the natural world with a fidelity we have never had before."
It also provided the down side: "Once you see the patterns you can understand the world's behavior. Once you understand behavior you can predict it. Once you can predict behavior you can control it. That is the true promise--and danger--of big data."
Despite the danger, NPR believes big cities and big data were made for each other, primarily because they are "engines of information." NPR gets equally poetic describing cities themselves as "created human environments … ecosystems of energy and matter imagined into existence through human effort." NPR says data scientists have a real opportunity to leverage all the data cities create to make them more efficient, effective and responsive to human needs. After all, in less than 40 years, 85 percent of the population will live in cities, the outlet said.
Big data can make cities adaptive and nearly self aware. It can address sustainability, security and public health. It can also relieve traffic problems, while at the same time identifying other issues related to or affected by traffic.
It can, but it hasn't yet. As pretty a picture as NPR paints of big data, other examples it gives, such as the tracking of influenza through Twitter, are not likely to be sustainable, reliable methods for tracking diseases or other issues requiring more scientific data.
Kate Crawford, researcher for Microsoft (NASDAQ: MSFT), says the idea that big data makes cities smart is a myth. She says big data is only as good as the people using it. Besides, with the reliance on data comes a detachment from the real issues, she said, as technologists tend to look at the data and devices, and not urban life.
In addition, data collected from devices, many of which are smartphones, can be discriminatory because not everyone in a city has access to smartphone technology. Likewise, people and systems would likely be tracked differently in different parts of a city.
- see the NPR article