Sofia Ranchordás: Cities as Corporations? The Privatization of Cities and the Automation of Local Law

This blogpost was first published on the Oxford Business Law Blog.

Cities throughout the world are becoming smarter thanks to AI, big data, Internet of Things (‘IoT’), and, more recently, blockchain.[1] Smart cities automate administrative decision-making with algorithms that decide, for instance, on building permits or social welfare applications.[2] Sensors spread throughout cities manage traffic congestion, cameras and algorithms control large crowds and try to detect suspicious actions.[3] As always, smart and innovative initiatives that result in a more efficient management of resources are highly appreciated. The smarter, the better. However, thus far scholars have overlooked an important element in this equation: private actors are often behind these innovative technologies and projects. Public-private partnerships or large technology companies develop smart solutions, assist civil servants with the collection and processing of data, shape the data analysis process, and, sometimes, fund new digital projects. [4] Nevertheless, the growing outsourcing of public services and the reliance on technology provided and controlled by private parties are currently in effect converting citizens into clients, cities into hybrid corporations, and private companies into their managers.[5]

In this article, I discuss the privatization of cities in the context of data-driven regulation and governance—that is, regulations and policies that draw directly or indirectly on big data and predictive analytics, including different types of AI, algorithms and cloud computing.[6]  I address three central issues raised by the implementation of disruptive technology in smart cities: first, the misalignment of interests between private actors behind smart technology and the public values that cities ought to protect; second, the privatization of citizenship; and third, the risks of employing private data-driven technology to nudge citizens.[7]


  1. Cities and Technology

The term ‘smart cities’ refers to geographical areas in which public officials implement data-driven technologies to create benefits for citizens in terms of inclusion and participation, environmental quality, and well-being.[8] The development and expansion of urban centres have been associated with technology since the Industrial Revolution.[9] Although the Romans already relied on then modern technology to develop water supply networks, it was only in the beginning of the nineteenth century that cities started struggling with significant urban organization problems.[10] While industrial cities in the 1800s struggled to build infrastructure to supply factories with raw materials and transport finished goods, cities in the twenty-first century struggle with the challenges of urban sprawl, the impact of globalization, and the need to promote more sustainable policies.[11] Smart cities are thus a modern example of the intimate connection between technology and urban development.

Smart cities have embraced data-driven technology to advance policing in urban centres, redesign urban planning and infrastructure, improve the reliability of public transportation, reduce accidents, and monitor energy consumption.[12] Despite the potential of disruptive technologies to improve the quality of public services, the employment of data science, big data, and predictive analytics in the regulation and governance of cities raises several legal and practical challenges. This is partially explained by the fact that smart cities rarely employ technology by themselves or developed by public bodies. Rather, technology control is primarily in the hands of private companies such as IBM, Google or Cisco. These companies provide cities with technologies that allow them to collect as much data as possible in order to better identify, understand and solve societal problems. The interference of these private actors in the growing automation of law and policy is far from being unproblematic, particularly at a time when local civil servants still have low levels of digital literacy and rely heavily on the codes and algorithms they are provided with, when making administrative decisions.[13] In a way, we are observing a direct or indirect form of privatization through technology that generates complex transparency and accountability problems.[14] The lack of transparency affects other longstanding legal institutions and procedural rights of citizens such as due process, freedom of information, non-discrimination, and fairness. [15]

While in the 1990s, privatization initiatives were often justified by resource savings in deregulated sectors or the need to involve more expert-based decision-making (e.g., certification of medical instruments), the privatization of smart cities is not always justified by similar goals.[16]


  1. Privatization

The privatization of smart cities comes in different shapes and sizes. It ranges from almost full private intervention and management of public spaces to the mere provision of technologies.[17] Gurgaon in India is possibly one of the most extreme and well-known examples of city privatization. Gurgaon was built almost entirely by private companies.[18] The city is developing sensors on garbage trucks and mobile apps for citizen engagement but, at the same time, Gurgaon does not have basic infrastructure such as a sewage system or electricity. Large companies and startups have luxurious offices in the city while former villagers have limited access to clean water and electricity. Gurgaon and several other modern cities are built for well-educated residents and visitors but not for all its citizens. The development of smart cities in developing countries might remind us of the ‘charter cities’ model pioneered by Paul Romer.[19] These semi-autonomous cities involve, nonetheless, partnerships between developed and developing countries, public and private actors, the creation of choices for citizens, and the generation of foreign investment opportunities in formerly uninhabited land.[20] By contrast, most ‘privatized’ smart cities throughout the world do not fulfill these criteria but they spark similar concerns such as the risk of capture by private actors, the development of large corporate projects rather than public utilities, and the danger of overlooking public values.[21]

Most smart cities that rely on the technology provided by large companies are not privatized to the extent of Gurgao. Instead, public-private partnerships are established, outsourcing contracts are designed, and companies are hired to develop specific technology for local authorities. The impact of privatization through technology on public values is, nonetheless, still visible, primarily on two levels: First, private actors provide technology through which citizen data can be collected and analyzed. Second, private technology reshapes the content, type of services and the access of citizens to them. In both cases, private initiatives and technology are currently redesigning the relationship between citizens and public bodies.[22]


  1. Citizen Empowerment or Marketization?

The first aspect of city privatization raises well-known legal issues. Citizens’ data have become a valuable asset that can be processed by predictive analytics technologies, enabling companies to use it for commercial profiling, targeted advertising, and credit risk calculation.[23] This raises questions regarding the ownership and management of data and the limits of outsourcing data collection to machine-learning processes managed or updated by private companies.[24] The General Data Protection Regulation aims to solve some of these problems but certainly not all of them (e.g., exchange of information between public bodies).[25]

The proponents of digital agendas often regard citizen data and other data-driven initiatives as instruments of citizen empowerment. This can indeed be true in the context of open government initiatives where technology is used to give a voice to citizens and promote their direct political participation.[26] Nevertheless, smart cities engage with citizen data for more purposes than simple ‘have your say-initiatives’. More often than not, citizens will participate involuntarily in data-driven regulation and governance by simply making certain commuting decisions instead of others (e.g., taking the bus rather the train).[27] Furthermore, this appearance of empowerment is also limited as several citizens are not always fully able to understand how the technology employed by smart cities can directly improve their quality of living and how it works in practice. In addition, citizens might have the feeling that even if they were provided with additional information, they would not be able to become wiser. A good example of the lack of transparency of this system is the consent forms that citizens are asked to fill in for the collection of their data. Refusing to give consent is always an option. Consumers can also choose not to consent to the gathering of data. However, how often does the average consumer do it? How many suitable alternatives would a citizen-consumer have, should she reject to have her data collected by a smart city? She can surely walk rather than use a smartcard for transportation. But where will she deposit her garbage bags when all the waste bins in her city require a personal card which is linked to her address?[28] There are of course privacy limitations to the analysis and collection of citizen data, but in the particular context of public services, it might be unwise to conceive citizens as consumers with alternatives.[29]  In many cases, citizens might simply consent to data collection because they are afraid of being excluded from certain services.[30]

The phenomenon of converting citizens into consumers has become particularly worrisome in developing countries (e.g., in India) where smart cities monetize on the commons and exclude a number of citizens who do not fit in their vision of what a smart city should look like.[31] Privatized cities might be tempted to invest in data-driven technology rather than in satisfying basic needs, for example of excluded communities. Moreover, despite the potential of big data for tailored decision-making, in a data-driven city, decisions are likely to be automated on the grounds of the rule of numbers.[32] Local customs are ignored and social enclaves are created because not all citizens are the tech-savvy individuals smart citizens would like them to be.[33] Moreover, the privatization of citizenship also creates room for greater surveillance and nudging.


  1. Nudging?

Public and private companies have been employing behavioural science for years to cue better decision-making (e.g., healthy eating habits through attractive default options).[34] Cities have also recently started using technology to nudge citizens in a wide array of policy areas, including water conservation, public health, environment, and revenue collection.[35] Nudging is often well-intended and typically tries to preserve citizens’ ability to choose. However, this choice architecture remains controversial, particularly when it is supported by obscure data-driven policies that citizens do not fully understand. If citizens do not know what data cities and private corporations have on them, they will not be given a real choice. Rather, nudging might interfere directly with citizens’ individual freedom not only because public bodies might be able to predict what their choices are, but also because the nudges will be shaped by corporate powers who might not always design them to pursue the public interest.[36]


  1. Conclusion

The technology employed by smart cities might convey the appearance of objectivity, higher transparency and accuracy in the processing of information. However, public administration and administrative law are still structured around spaces of discretion—human discretion—which should be guided by the principles of transparency and accountability. The unregulated automation of administrative decision-making is, nonetheless, not the only menace to public values. Instead, cities should rethink their alliance with private actors and their ability to fully understand how technology works, what data is collected, and what values underlie the code of data-driven technology. The reliance of smart cities on data-driven technology fits within the broader trend to corporatize, privatize, contract-out and outsource public tasks to third parties.[37] Nevertheless, it is about time local governments regain control over their digital services, improve digital literacy in the public sector, devote more attention to automated procedures, and rethink the relationship between citizens, smart cities, and technology.[38]

Sofia Ranchordás (L.L.M, PhD) is a Professor of European and Comparative Public Law and a Rosalind Franklin Fellow at the University of Groningen in the Netherlands and an Affiliated Fellow of Information Society Project at Yale Law School. Her research delves into the relationship between public and private bodies and the role of technology therein, the regulation of the peer-to-peer networks, online reputational systems, digital participation and democratic legitimacy, and smart cities. Her scholarship includes a book on experimental legislation, a book on administrative discretion, and a number of articles published in international peer-reviewed and U.S. law journals on law and technology. She has held previous teaching positions at Leiden University and Tilburg University, she has been a Visiting Scholar at the George Washington University Law School and the University of International Relations (China). She is the recipient of both national and international research grants.

[1] There is a growing body of literature on smart cities and digitalization. See, e.g., Annalisa Cocchia, Smart and Digital City: A Systematic Literature Review (Springer 2014); Lilian Edwards, ‘Privacy, Security and Data Protection in Smart Cities: A Critical EU Law Perspective’ (2016) 2 European Data Protection Law Review 28; Rob Kitchin, ‘The Real-Time City? Big Data and Smart Urbanism’ (2014) 78 GeoJournal 1; Anthony M. Towsend, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia (W. W. Norton 2013); Stephen Goldsmith and Susan Crawford, The Responsive City: Engaging Communities through Data-Smart Governance (Wiley & Sons 2014). See also Duncan McLaren and Julian Agyeman, Sharing Cities: A Case for Truly Smart and Sustainable Cities (MIT Press 2015).

[2] Andrew Le Sueur, ‘Robot Government: Automated Decision-making and its Implications for Parliament’ in A. Horne & A. Le Sueur (eds), Parliament: Legislation and Accountability (Hart Publishing 2016).

[3] Andrea Caragliu, Chiara Del Bo and Peter Nijkamp, ‘Smart Cities in Europe’ (2011) 18 (2) Journal of Urban Technology 65.

[4] Graeme Laurie and Leslie Stevens, ‘Developing a Public Interest Mandate for the Governance and Use of Administrative Data in the United Kingdom’ (2016) 43(3) Journal of Law and Society 360.

[5] Linnet Taylor and others, ‘Customers, Users or Citizens? Inclusion, Spatial Data and Governance in the Smart City’ (2016) <> accessed 19 March 2018; Pernille Hohnen and Torbjörn Hjort, ‘Citizens as Consumers’: A Discussion of New Emergent Forms of Marginalisation in the Nordic Welfare States’ (2009) 11 European Journal of Social Security 271, 274.

[6] John Danaher and others, ‘Algorithmic Governance: Developing a Research Agenda through the power of Collective Intelligence’ (2017) Big Data & Society 1. See also Cary Coglianese and David Lehr, ‘Regulating by Robot: Administrative Decision Making in the Machine-Learning Era’ (2017) 105 Georgetown Law Journal 1147, 1152.

[7] On the misalignment of public and private interests, see, e.g., Ellen Dannin, ‘Red Tape or Accountability: Privatization, Publicization, and Public Values’ (2005) 15 Cornell Journal of Law & Public Policy 111; Jody Freeman, ‘The Contracting State’(2000) 28 Florida State University Law Review 155; Jody Freeman, ‘Private Parties, Public Functions and the New Administrative Law’(2000) 52 Administrative Law Review 813. On automated decision-making and accountability, see, e.g., Joshua A. Kroll and others, ‘Accountable Algorithms’ (2017) 165 University of Pennsylvania Law Review 633, 654. On the duty to give reasons, see, e.g., Lilian Edwards and Michael Veale, ‘Slave to the Algorithm? Why a ‘Right to an Explanation’ is Probably Not the Remedy You Are Looking for’ (2017) 16 Duke Law & Technology Review 18, 43.

[8] The definition of ‘smart cities’ is highly contested and there is no consensual agreement on its definition. For an overview of the literature, see Annalisa Cocchia, Smart and Digital City: A Systematic Literature Review (Springer 2014).

[9] Gerrylynn K. Roberts, ‘The Growth of Cities’ in Gerrylynn K. Roberts and Philip Steadman (eds), American Cities & Technology: Wilderness to Wired City (Routledge 1999) 15; Nina E. Lerman, ‘Books on Early American Technology, 1966-1991’ in Judith A. McGaw (ed.), Early American Technology: Making and Doing Things from the Colonial Era to 1850 (University of North Carolina Press 1994) 385

[10] Peter Hall, Cities in Civilization (Fromm International, 1998) 16.

[11] Scott Page, Brian Philips and Walter Siembab, ‘The Millennium City: Making Sprawl Smart through Network-Oriented Development’ (2003) 10(3) Journal of Urban Technology 63; Robert Bruegmann, Sprawl: A Compact History (University of Chicago Press 2005) 24.

[12] Anthony M. Towsend, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia (W.W. Norton & Company 2013) 93-94; Nir Kshetri, ‘The Emerging Role of Big Data in Key Development Issues: Opportunities, Challenges, and Concerns’ (2014) 1 Big Data & Society 1; Graeme Laurie and Leslie Stevens, ‘Developing a Public Interest Mandate for the Governance and Use of Administrative Data in the United Kingdom’ (2016) 43 Journal of Law & Society 360, 361; Laura Aelenei and others, ‘Smart City: A Systematic Approach towards a Sustainable Urban Transformation’ (2016) 91 Energy Procedia 970.

[13] Andrew Guthrie Ferguson, ‘Policing Predictive Policing’ (2017) 94 Washington University Law Review 1115.

[14] Lilian Edwards, ‘Privacy, Security and Data Protection in Smart Cities: A Critical EU Law Perspective’ (2016) 2 European Data Protection Law Review 28, 31, 32. See generally on big data and transparency, Frank Pasquale, The Black Box Society: The Secret Algorithms that Control Money and Information (Harvard University Press, 2015); Danielle K. Citron and Frank Pasquale, ‘Technological Due Process’ (2008) 85 Washington Law Review 1249.

[15] Danielle Keats Citron & Frank Pasquale, ‘The Scored Society: Due Process for Automated Predictions’ (2014) 89 Washington Law Review 1; Danielle Keats Citron, ‘Technological Due Process’ (2007) 85 Washington University Law Review 1249.

[16] Michael Abramowicz, ‘Information Markets, Administrative Decisionmaking, and Predictive Cost-Benefit Analysis’ (2004) 71 University of Chicago Law Review 933, 964.

[17] See generally on the privatization of public services, Mike Raco, State-led Privatisation and the Demise of the Democratic State (Routledge 2013).

[18] Vidhi Doshi, ‘Gurgao: What Life is Like in the Indian City Built by Private Companies’, The Guardian, July 4, 2018, available at

[19] Paul Romer, ‘For richer, for poorer’ Prospect, January 27. <> Accessed 02.10.12.

[20] Romer’s charter city idea appears to be partially inspired by Hong Kong. The qualification of Hong Kong as a charter city is, nevertheless, not widely accepted, see, e.g., Kee-Cheok Cheong & Kim-Leng Goh, ‘Hong Kong as Charter City Prototype: When Concept Meets Reality’, Cites, 35: 100 – 103.

[21] Sandy Ikeda, ‘Are “Charter Cities” a Solution?’, Foundation for Economic Education, April 20, 2010, available at

[22] Rory van Loo, ‘Rise of the Digital Regulator’ (2017) 66 Duke Law Journal 1267, 1273; Stephen Goldsmith and Susan Crawford, The Responsive City: Engaging Communities through Data-Smart Governance (Wiley 2014) 3, 27.

[23] Guido Noto La Diega, ‘The Internet of Citizens: A Lawyer’s View on Some Technological Developments in the United Kingdom and India’ (2016) 12 The Indian Journal of Law and Technology 53, 56.

[24] Lilian Edwards, ‘Privacy, Security and Data Protection in Smart Cities: A Critical EU Law Perspective’ (2016) 2 European Data Protection Law Review 28, 31, 32.

[25] For a critical perspective see, for example, Bert-Jaap Koops & Ronald Leenes, ‘Privacy Regulation Cannot Be Hardcoded. A Critical Comment on the ‘Privacy by Design’ Provision in Data-Protection Law’ (2014) 28 International Review of Law, Computers & Technology 159; Mireille M. Caruana, ‘The Reform of the EU Data Protection Framework in the Context of the Police and Criminal Justice Sector: Harmonisation, Scope, Oversight and Enforcement’(2017) International Review of Law, Computers & Technology, DOI:; Maria Eduarda Gonçalves, ‘The EU Data Protection Reform and the Challenges of Big Data: Remaining Uncertainties and Ways Forward’(2017) 26 Information & Communications Technology Law 90

[26] Beth Simone Noveck, Smart Citizens, Smarter State: The Technologies of Expertise and the Future of Governing (Harvard University Press 2015); Beth C. Weitzman, Diana Silver and Caitlyn Brazill, ‘Efforts to Improve Public Policy and Programs through Data Practice: Experiences in 15 Distressed American Cities’ (2006) Public Administration Review 386, 387.

[27] Beth C. Weitzman, Diana Silver and Caitlyn Brazill, ‘Efforts to Improve Public Policy and Programs through Data Practice: Experiences in 15 Distressed American Cities’ (2006) Public Administration Review 386, 387. See also Simone Noveck, ‘‘Peer to Patent’’: Collective Intelligence, Open Review, and Patent Reform’ (2006) 20 Harvard Journal of Law & Technology 123. See also, from a broader perspective, Margaret Scammell, ‘The Internet and Civic Engagement: The Age of the Citizen-Consumer’ (2010) 17 (4) Political Communication 351.

[28] This is the case in many Dutch cities. The Dutch city of Arnhem recently announced that the city council would give up the controversial rubbish-cards as of January 2018 as they raised numerous privacy concerns. The Dutch Data Protection Authority sanctioned the city in 2017 as the sensors were used to process citizen data that was not strictly necessary for the exercise of a public task. Many other cities employ sensors in smart waste bins, see,e .g., Rob Kitchin, ‘The Real-time City? Big Data and Smart Urbanism’ (2014) 79 GeoJournal 1,5.

[29] Pernille Hohnen and Torbjörn Hjort, ‘Citizens as Consumers’: A Discussion of New Emergent Forms of Marginalisation in the Nordic Welfare States’ (2009) 11 European Journal of Social Security 271, 274; Tobias Jung, ‘Citizens, Co-producers, Customers, Clients, Captives? A Critical Review of Consumerism and Public Services’ (2010) 12 Public Management Review 439.

[30] Linnet Taylor and others, ‘Customers, Users or Citizens? Inclusion, Spatial Data and Governance in the Smart City’ (2016) <> accessed 9 February 2018.

[31] Ayona Datta, ‘Will India’s Experiment with Smart Cities Tackle Poverty—or Make it Worse?’, The Conversation, 27 January 2016, available at

[32] See generally, Alain Supiot, Governance by Numbers: The Making of a Legal Model of Allegiance (Bloomsbury 2017).

[33] Katherine Harrison, ‘Who is the Assumed User in the Smart City?’ in Vangelis Angelakis and others (Eds.), Designing, Developing, and Facilitating Smart Cities: Urban Design to IoT Solutions (Springer 2017) 17.6

[34] Richard H. Thaler and Cass R. Sunstein, Nudge: Improving Decisions about Health, Wealth, and Happiness (Penguin 2009); Richard H. Thaler, Misbehaving: The Making of Behavioral Economics (W.W. Norton & Company 2016).

[35] Karen Yeung, ‘The Forms and Limits of Choice Architecture as a tool of Government’ (2016) 38(3) Law & Policy 186.

[36] Neil M. Richards and Jonathan H. King, ‘Three Paradoxes of Big Data’ (2013) 66 Stanford Law Review Online 41, 44.

[37] On local corporatization, see, e.g., Giuseppe Grossi & Christoph Reichard, ‘Municipal Corporatization in Germany and Italy’ (2008) 10 Public Management Review 597.

[38] Patrick Dunleavy, Helen Margetts, Simon Bastion & Jane Tinkler, ‘New Public Management Is Dead—Long Live Digital-Era Governance’ (2006) 16(3) Journal of Public Administration Research and Theory 467.

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