Viktor Mayer-Schönberger: what role does big data play in cities?

In a few years’ time, two thirds of people will live in urban areas. Clearly, appropriate policies must be conducted to support this change. For political leaders and urban planners, this involves making key decisions for the future of cities and tackling choices that are sometimes difficult and with huge implications. “Smart cities” gave rise to the hope of at last having an effective decision-making tool, used to justify decisions with a solid basis of collected data rather than an instinct which may prove wrong. The more we collect data, the easier it will be for us to make the right decisions. As we have inherited the spirit of the Enlightenment, we are all striving to take action in view of fact-based data.

For many, data is an additional tool which facilitates city administration, but for me, it is much more than a simple technological tool.

How can data collection be used in the administration of urban areas?

Data collected gives us the opportunity to gain a more specific knowledge of practices in the city. Let us take the example of the state of infrastructure: in Vienna, data is collected on users’ Smartphones – in this case, vibrations –to locate the train tracks which need to be improved. Data collection therefore brings about a better maintenance of infrastructure, which is more targeted and therefore faster, in addition to enhanced services for users.

Data also allows us to adapt to each situation and to only make decisions which consider the specific characteristics of each case. Let us look at medicine for a moment. If I feel unwell and take some aspirin, I am making a big mistake. The tablet was designed to treat a typical male adult and I, like you, am far from typical. I am original and unique. Data is used to deal with this uniqueness. Thanks to data, we could change the way in which medication is prescribed, to develop a more precise medical system and improve quality of life.

Lastly, data plays a key role in policies that aim to change certain lifestyles, in particular mobility policies which can require colossal investments. Data is used to make the right investments, at the right time and in the right place. Take autonomous cars for example. Google was not the first to develop such vehicles and yet, while in 2015 an autonomous car by a conventional car manufacturer was able to travel 400 km before requiring human intervention, the Google car was already covering more than 2000 km. Why is this? Because Google adopted a different approach, based on big data. Its autonomous vehicles are fitted with sensors which collect a huge amount of data which is processed constantly to improve the system and find swift solutions to problems that arise.

This data can be collected and leveraged by many stakeholders with different interests and represents a real challenge for cities and their infrastructure in particular. Take Uber, which has disrupted conventional transportation infrastructure by developing a mobility system in which individual transportation can be on-demand, giving users greater flexibility in their travel. Ultimately, yes, data is promising and useful in the administration and design of a city. Yet we must go further and consider what it will be used for, for what purpose and how it will change the way we think.

Moreover, we must be aware that data and knowledge do not suffice to provoke change. Mentalities must also be totally transformed. My colleagues at the London School of Economics have calculated that if people shared their cars more, we could reduce the space required for parking by 20 to 30%…. Yet, 70% of the Austrians that I know think that their car is too precious to be shared with someone else. I drive much better than other people, that’s a fact!

How can we know if our decision-making process is based on the right data? What is the role of big data in this? How can we deal with this mass of information?

The abundance of data collected is not a disadvantage, it’s a good thing. Prior to big data, the data to be collected had to be sorted.  A focal point was selected, very often the initial question for which the collection operation was set up, exactly like when I take a photo. I need to choose a focal point. Once that point is selected, I cannot change it. A photo taken along the lines of big data works differently. I can keep all data collected as I only choose a focal point once the photo is taken. I can therefore change it as required and can even select two focal points at the same time. This actually means that I can use data for which I had not initially perceived a use because I did not exclude it when I started collecting. Massive data collection gives us the chance to change the question as our research progresses. This is one of the main advantages of data. Often, academics collect data, analyse it and observe that the initial question was not right. The entire process has to be started again from scratch in this case. This problem is avoided by collecting data with a broader focal point. Big data is another scientific research method that is no longer based on hypotheses to be confirmed or invalidated but on simple correlation: algorithms reveal the models or indicate failings on the basis of a statistical analysis of big data. Let us take a concrete example: prematurely-born babies often die of infections that are detected too late. In Canada, a team of researchers fitted sensors that collect 200 data items per second on the babies. They let the data express itself and, in this way, developed a counter-intuitive model that can predict infections so they can be treated in time: the premature baby is in danger when its vital functions stabilise … This slightly crazy example is what makes this era of big data fascinating.

What are the applications for cities?

Cities are places with a high concentration of people. A city that operates well is a city that is buzzing, with multiple stakeholders taking action and making decisions. How can they be coordinated? How can such spaces be governed, when they may appear unmanageable? Which governance system should be adopted? Administrators have found a solution in the advent of the smart city: data was going to help them to understand the complex functioning of the urban ecosystem, to predict it and therefore chart it.

Big data is a real asset for governance, in terms of the planning it makes possible but even more through the data processing operations it facilitates. With data, governance can be considered as a discussion within which planners have a different role. The aim is no longer to develop set concepts to be applied but rather to make changes to them gradually on the basis of information provided by data. Big data favours the construction of a more flexible city.

There are doubts regarding the use of data and there is an increasing focus on privacy. As cities are inexperienced in the use of data and inhabitants know little about the way in which their data can be collected and processed, a certain mistrust is noticeable. How can trust be built?

It takes time for trust to be established… However, cities are naturally responsible for the way they use collected data. Trust can be built by creating cities that function well and do not waste money. This is achieved through governance systems based on data use. Citizen involvement must also be encouraged – in ways that are yet to be identified and which must be adapted to each city. Data is only the raw material of the discussion, not the medium which fosters dialogue.