Designer & Technologist


(Not So) Smart City

Perils of data-driven approach to urban planning

Today, over half of the world’s population lives in urban areas, with the proportion expected to increase to two thirds by 2050 (United Nations, 2014). Old models and ideals of urban planning seem inadequate for the contemporary cities where “the spaces and rhythms are radically different to those described in classic theories of urbanism” (McQuire, 2008, p. vii). The idea of the smart city has come to guide urban planners in their efforts to apply technology to cope with increasingly complex cities.

This paper argues that existing approaches to smart city design are rooted in a techno-centric mindset that is not suitable for urban problems that are inherently social. The paper first examines the problematic aspects of the current smart city discourse. It then critically analyses underlying principles of the dominant data-driven smart city ideology, followed by an alternative vision of smart city based on citizen engagement.

Demise of the smart city discourse

In a broad sense, smart cities can be described as places where information technology is combined with infrastructure, architecture, and everyday objects to address social, economic, and environmental problems (Townsend, 2013). Other closely related concepts include ubiquitous computing, ambient intelligence, ambient informatics, urban informatics, internet of things, sentient city, or computerised spaces (Graham, 2005; Greenfield, 2006; Waal, 2011). The range of terms illustrates the absence of a single point of origin of the smart city ideal.

The lack of consensus surrounding the concept of the smart city makes the term bloated with various connotations depending on the target audience and thus devoid of any particular meaning or interpretation. The smart city has become a de facto shorthand for multinational ICT and infrastructure companies to promote their products to a global market of cities desperate for comprehensive solutions to increasingly pressing urban issues (Batty et al., 2012). This “mainly business oriented message of the smart cities movement” (Batty, 2013, p. 11) has lead Adam Greenfield, one of the most vocal critics of the contemporary smart city rhetoric, to declare an intellectual bankruptcy of the vision of the smart city (Greenfield, 2017). Greenfield (2013) goes as far as to suggest that the term appears to have originated with business “rather than with any party, group or individual, recognised for their contributions to the theory or practice of urban planning” (par. 22).

The dominant smart city narrative focuses primarily on the technology, cost-effectiveness, and relentless optimisation in an attempt to impose a vision of clean, computed, centrally managed urban order (Townsend, 2013). This approach is reminiscent of the paternalistic top-down city planning ideology of the second half of the 20th century so eloquently exposed by Jane Jacobs (1961). Similarly to how the aerial imagery inspired the design of mega-scale modern cities, smart city designs today are guided by an expanding data collection capabilities that offer increasingly robust computational analysis of minute details of lives of city dwellers (Batty, 2012; Greenfield, 2006; Towsend, 2013). The next section critically examines some of the ideological underpinnings, assumptions, and challenges posed by this data-driven approach to urban planning.

A false promise of a sentient city

Most of the existing smart city conceptualisations are entirely predicated on “ubiquitous, pervasive and interlinked arrays of computerized spaces” that continuously collect and analyse data from an increasingly sophisticated sensory apparatus embedded in the urban fabric (Graham, 2005). As city planners rely more and more on data aggregated by such systems, it raises thorny issues of the nature of data and how is it used to inform the urban planning processes.

Significant advances in big data analysis and machine learning are pushing organisations to embrace data as the core component of their operations to a degree where data is fetishised as something inherently objective and non-political (Greenfield, 2017; Han, 2017). The unstated assumptions about the nature of truth contained within the data or its potentially dubious origins rarely come under severe scrutiny despite the significant implications for public decision making and urban development (Goodspeed, 2012; Townsend, 2013).

Every mathematical model of the real-world phenomena is inherently an approximation. While such models are useful for analysis and improving understanding, they should be considered as a diagnostic tool, a means to an end, rather than the underlying mechanism permeating the fabric of the city. Models and computer simulations seduce smart city designers because they replace the complexity of the real city with models that disregard the subjective reality of citizens and leave out the peculiar way groups make decisions (Townsend, 2013). According to one of the prominent contemporary critics of technological utopianism Evgeny Morozov (2010) “[p]art of the problem seems to lie in the public’s penchant for fetishizing the engineer as the ultimate savior, as if superb knowledge of technology could ever make up for ignorance of local norms, customs, and regulations” (2010, par. 10).

The data-driven approach to smart cities reduces people with their unique personalities and rich cultural backgrounds to a stream of standardised data to be treated as interchangeable statistics (Greenfield, 2013; Jacobs, 1961). In this schema, the role of the citizen “is simply to generate data that can be aggregated and subjected to analytical inquiry” (Greenfield, 2013, par. 7). However, according to Townsend’s (2013) interview with Michale Batty “[a] lot of the old questions which you’d think might be informed by new data are not” (p. 315).

The model of the smart city outlined above is rooted in a technocentric engineering mindset that strives above all for optimisation, efficiency and by extension for uniformity. By seeking to rid themselves of every possible inefficiency, cities risk losing the diversity and vigour that are so characteristic of them – ultimately leading to a colonisation and mechanisation of everyday life by information technology (Greenfield, 2006; Townsend, 2013). However, this approach to urban management is incompatible with the assertion of leading researchers in the field of science of cities which admit that “our science has become less orientated to prediction but more an aid to understanding, to structure debate“ (Batty & Torrens, 2001, p. 3).

The glorification of the engineering culture and its focus on the capabilities of the latest technology, most apparent in the field of ICT, is also a staple in the data-driven view of the smart city. In this perspective, cities are seen as a software problem where the primary concern is with the underlying code which is taken at face-value as something intrinsically objective and neutral. However, this overly deterministic view disregards the fact that values, opinions, biases, and rhetoric are frozen into code (Bowker & Leigh-Start, 2000). Moreover, “intractable properties of certain kinds of technology are strongly, perhaps unavoidably, linked to particular institutionalized patterns of power and authority” (Winner, 2003, p. 134). With computational capabilities dissolving deeper into the background of everyday life, exposing the cultural and spatial politics of code present a significant challenge for the future of smart city planning (Graham, 2005; Townsend, 2013).

It is essential to look at the technology embedded in cities not just as objects but also as knots of social, economic and political interest (Batty, 2013; Puig de la Bellacasa, 2011). The technodeterministic perspective outlined above is part of a broader tendency to put a combination of neoliberal, consumeristic principles and ideologies of governance at the centre of the smart city discourse (Graham, 2005). This rhetoric is guided by the reductionist mentality of dataism - an ideology that asserts that the entire universe is comprised of data flows and the value of any phenomena or entity is measured by its capability to contribute to data processing, including the value of a human life (Han, 2017; Harari 2017). Within such context, the “data-driven management for cities is an irresistible fiscal force shaping the future” of commodified and individualised spaces (Graham, 2005; Townsend 2013).

Technology firms designing smart cities solutions are increasingly “making choices, about technology, business, and governance, with little or no input from the broader community of technologists, civic leaders, and citizens themselves” (Townsend 2013, p. 110). Their profit-driven view of the city puts forth a vision of a neoliberal city of governance-as-a-service in which personalised infrastructural services treat citizens as individual customers (Greenfield, 2013; Waal, 2011). Such conception of the smart city leads “towards the 'splintering’ of the sociotechnical and geographical fabric of contemporary cities” (Graham, 2005, p. 576) and a development of business models for a fully privatised city (Greenfield, 2013). And since “[w]hoever owns this layer of proprietary protocols and infrastructure will truly hold the keys to the city”, local governments are effectively handing over the control over their urban affairs to private business interests (Townsend 2013, p. 290).

Provisioning of cities with a vast sensory and data processing capabilities also raises critical issues of power dynamics. Informatic and biometric modes of surveillance permitted by ubiquitous computational awareness allow power to move at the speed of an electrical signal (Baumann & Lyon, 2012). The pervasive extension of power into public space poses a danger of a panoptical surveillance that constrains behaviour at the level of architecture (Baumann & Lyon, 2012; Greenfield, 2013). Such “code-based technologized environments continuously and invisibly classify, standardize, and demarcate rights, privileges, inclusions, exclusions, and mobilities and normative social judgments across vast, distanced domains” (Graham, 2005, p. 563). Inequal access to data generated by these vast structures puts citizens, particularly poor communities, at the mercy of those who can measure and control from a distance (Cinnamon, 2017; Goodspeed, 2012; Townsend, 2013).

The vision of all-seeing sentient city driven by business interests poses a danger of creating private cities, exuberating inequality and social polarisation by creating a ‘capsular society’ dominated by the cultures and biopolitics of separation and continuous digital filtering and tracking (Batty, 2013; Comer, 2011; Graham, 2005). This conquest of everyday life through a ubiquitous analysis of geolocated patterns of life epitomises an advanced form of society of control where control is short-term, continuous and without limit (Deleuze, 1992; Greenfield, 2006). A city that tracks and controls its citizens is not a smart city, but an authoritarian one.

Technocratic principles outlined here are already being put to use in supposedly exemplary smart city designs around the world. Songdo in South Korea and Masdar in the United Arab Emirates are entire new city districts being built around the principles on a data-driven urban operating system that offers a “high-precision control panel for the entire city” (Townsend 2013, p. 67). In Rio De Janiero, IBM has built an operations centre for local government that, in the words of Rio’s then major Eduardo Paes, “allows us to have people looking into every corner of the city, 24 hours a day, 7 days a week” (Townsend 2013, p. 67). The way these projects are currently imagined, ”not one of the canonical smart cities seems as if it might be capable of supporting a usefully differentiated human ecology” (Greenfield, 2013).

Towards smart civics

The previous section paints an Orwellian picture of the future of smart cities. There is, however, an alternative vision that treats “smart as an add-on, an upgrade, and not the end itself” (Townsend, 2013, p. 286). In this perspective, smart cities are conceptualised at the scale of an individual and focus on small-scale tactical urban interventions rather than grand city-wide schemes (Townsend, 2000; Townsend 2013). It is an approach that sensitively leverages advanced technology but is not driven by it, to create platforms for localised citizen micro-control of the physical environment (Greenfield, 2017; Townsend, 2013).

Networked technologies allow the decision-making power to be pushed closer to the people being most affected by the local urban development. By treating citizens as agents of change, novel forms of participatory urbanism enable better collective approaches to decision-making (Batty et al., 2012; Paulos, n.d.). Support of grassroots efforts for urban self-governance empowers citizenry to help themselves through distributed technology, as opposed to imposing centralised technocratic structures on them. Such micro-scale transformative processes aim to preserve local cultural diversity while improving the wellbeing of the city as a whole.

The 20th century has witnessed a culmination of centuries worth of knowledge about vernacular structures and construction best practices which have been distilled into accessible compendiums. Misguided by the capabilities of the latest technology, the contemporary smart city rhetoric misses the fact that “many problems can be adequately addressed simply by conventional design” (Townsend, 2013, p. 286). Books such as Patten Language (Christopher et al., 1977), detailing generation-tested best practices for construction of homes and cities, or Design for the Real World (Papanek, 1972), presenting a framework for socially responsible design, offer anyone an opportunity to have a more constructive relationship to the built environment around them.

The challenge for future smart city designs is not so much a matter of coming up with ground-breaking technological solutions, as it is a matter of improving communication and knowledge sharing across local communities, governments and professional industries. Integration and coordination of individualised and localised technology can lead to a synergy of personal and professional knowledge that will be necessary to build thriving cities in the future. Such approach “must involve ways in which the citizenry is able to participate and to blend their personal knowledge with that of experts” (Batty et al., 2012, p. 485).

Wireless mobile technology presents a yet untapped potential for participatory urbanism. Smartphones, in particular, have become an essential cognitive prosthetic for city dwellers all around the world. These smart handheld devices augment many aspects of life in large cities by “reprogramming the basic rules of interaction for urban inhabitants” through various sensors and geolocation capabilities (Townsend 2000, p. 100). Hospitality, taxi, and food services are some of the industries getting most disrupted by platforms such as Airbnb, Uber, and Foursquare. Admittedly business-oriented, these platforms illustrate the potential of mobile technology to significantly alter the everyday experience of people living in cities. Despite the rapid growth in the number of smartphone users across the globe, urban planners and policymakers have not kept pace with the industry and are slow to sensibly incorporate these devices into their designs and processes.

Most attempts to leverage mobile technology to improve citizen participation originate with grassroots efforts lead by well-intentioned hobbyists and technologists. Such projects manage to showcase the potential of decentralised forms of decision-making by temporarily engaging citizens, professionals and local governments in a joint urban design process. Unfortunately, they tend to gradually taper off due to the lack of sustained long-term development and timid political will to incorporate these novel modes of governance into an existing formal framework for city planning. Moreover, successful experiments in decentralised urban innovation are hard to scale up to the city level due to their localised nature.

Governments tackling massive socioeconomic issues are reluctant to invest in small-scale projects with questionable outcomes. In their view, they cannot afford to rely on groups of enthusiasts tinkering with gadgets to solve their urban ills and instead call for the might of “sustained industrial engineering applied to replumb entire cities over the span of a decade” (Townsend 2013, p. 165). Governments, pressed for time and resources, cling to one-size-fits-all quick fixes that neglect the complex and intricate social fabric of the city. Looking back at the urban development in the 20th century, “it is of utmost importance in setting the smart cities agenda in the wider social context without which we are destined to repeat the physicalist mistakes in the past planning of our cities” (Batty, 2013, p.26).


This paper illustrates that the primary challenge facing smart cities today is not technical but cultural (Comer, 2011). Researchers and designers need to create a more coherent narrative of the smart city to “to counter the rationalist city models tailored to the consumerist logic of the ‘society of spectacle’ with an approach centered on subjective experiences of the city, including areas and experiences marginalized in the dominant way of thinking about urban culture” (Waal, 2011 p. 10). A new social code stemming from an ideology of “socially conscious urban citizen” (Foth et al., 2011, p. x) demands a “clear synthesis of hardware, software, database, and organisational technologies that are able to relate to the key problems of society and will require entirely new methods and models for synthesising diverse data and ideas that are currently not being addressed” (Batty et al., 2012, p. 484). In the words Michael Joroff from MIT: “Master plans will give way to master strategies” (as cited in Townsend 2013, p. 305).

The analytical and political challenge is thus to excavate and critically assess underlying assumptions and ideologies of the contemporary smart city discourse to inform more sensible and inclusive models for truly smart cities. Further research into the decentralised modes of governance and citizen engagement is necessary.


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