Questioning Smart Urbanism: Is Data-Driven Governance a Panacea?

In the era of data explosion, urban planners are increasingly relying on real-time, streaming data generated by “smart” devices to assist with city management. “Smart cities,” referring to cities that implement pervasive and ubiquitous computing in urban planning, are widely discussed in academia, business, and government. These cities are characterized not only by their use of technology but also by their innovation-driven economies and collaborative, data-driven city governance. Smart urbanism can seem like an effective strategy to create more efficient, sustainable, productive, and open cities. However, there are emerging concerns about the potential risks in the long-term development of smart cities, including political neutrality of big data, technocratic governance, technological lock-ins, data and network security, and privacy risks.

In a study entitled, “The Real-Time City? Big Data and Smart Urbanism,” Rob Kitchin provides a critical reflection on the potential negative effects of data-driven city governance on social development—a topic he claims deserves greater governmental, academic, and social attention.

In contrast to traditional datasets that rely on samples or are aggregated to a coarse scale, “big data” is huge in volume, high in velocity, and diverse in variety. Since the early 2000s, there has been explosive growth in data volume due to the rapid development and implementation of technology infrastructure, including networks, information management, and data storage. Big data can be generated from directed, automated, and volunteered sources. Automated data generation is of particular interest to urban planners. One example Kitchin cites is urban sensor networks, which allow city governments to monitor the movements and statuses of individuals, materials, and structures throughout the urban environment by analyzing real-time data.

With the huge amount of streaming data collected by smart infrastructure, many city governments use real-time analysis to manage different aspects of city operations. There has been a recent trend in centralizing data streams into a single hub, integrating all kinds of surveillance and analytics. These one-stop data centers make it easier for analysts to cross-reference data, spot patterns, identify problems, and allocate resources. The data are also often accessible by field workers via operations platforms. In London and some other cities, real-time data are visualized on “city dashboards” and communicated to citizens, providing convenient access to city information.

However, the real-time city is not a flawless solution to all the problems faced by city managers. The primary concern is the politics of big, urban data. Although raw data are often perceived as neutral and objective, no data are free of bias; the collection of data is a subjective process that can be shaped by various confounding factors. The presentation of data can also be manipulated to answer a specific question or enact a particular political vision.

Another concern Kitchin discusses is that people tend to overestimate the power of data analysis. A data-driven and algorithmic approach is not necessarily an effective way to solve complicated city issues. Data alone does not address the root cause of problems that cities face. Moreover, the ostensible reliability of data analytics can become a convenient excuse for poor policy decisions. When a policy does not work well, the policymaker can say, as Usman Haque puts it, “It’s not me; it’s the data!”

As smart urbanism is partially driven by technology vendors, some are concerned that city governance is overtly shaped by corporate interests. Kitchin notes that government reliance on particular technology vendors creates a technological lock-in. These long-term dependencies can lead to monopolies. Also, a universally applicable platform created by a single vendor might not effectively meet the unique needs of different cities.

Concerns over system security stem from the increasing reliance of city operations on software. Smart cities are highly dependent on software to function, making city management systems vulnerable to the high security risks associated with software and networks. This concern is becoming more central as operational alternatives to software are gradually disappearing.

Finally, smart cities encroach on individual privacy. Gathering more data requires a higher level of governmental surveillance of citizens’ daily lives. It is possible to track and trace individuals and their actions in almost every aspect of their lives with a real-time, data collection system. Within a “culture of control,” it is also desirable to do so. According to Kitchin, this poses a significant threat to privacy, confidentiality, and freedom of expression.

Considering the rapid proliferation of smart urbanism, now is the right time to investigate the nature of urban big data and the implications of technocratic governance. Big data and smart technologies should be complemented with effective regulations and policies to fulfill their potential for creating better cities.

Article Source: Kitchin, R. (2014). “The Real-Time City? Big Data and Smart Urbanism.” GeoJournal, 79(1), 1-14.

Feature Photo: cc/(Reto Fetz)