Book Review: The Smart Enough City

Amidst the cacophony surrounding smart cities, cities could do just fine being ‘smart enough’

Book Review: The Smart Enough City: Putting Technology In Its Place To Reclaim Our Urban Future

Author: Ben Green (MIT Press, 2019)

The rhetoric of smart cities pervades visions of future cities, giving rise to the perception that every urban issue can and should be resolved with the help of technology. As a result, people, companies and governments are eager to develop and adopt new technologies intended to make society more ‘efficient’, ‘connected’ and ‘optimised’—buzzwords through which the ‘smart city’ often juxtapositions itself against the ‘dumb city’.

In The Smart Enough City, Ben Green points out that the techno-solutionism fuelling the rise of the ‘smart city’ is grounded on two beliefs: first, that technology provides value-neutral and optimal solutions to social problems, and second, that technology is the primary mechanism of social change. When we conceive of every issue as a technology problem, we entertain technical solutions at the cost of dismissing other possible remedies. In doing so, this approach masks political and social decisions as objective, technical ones.

Green warns against seeing the city only through the lens of technology. Taking an exclusively technical view of urban life may lead to cities that appear smart but under the surface are rife with injustice and inequality. Pointing to the false dichotomy of the smart city and the dumb city, Green emphasises the need to develop an alternative vision—that of Smart Enough Cities. Being ‘smart enough’ entails embracing technology as a powerful tool to address the needs of urban residents, in conjunction with other forms of non-technological innovation and social change. Rather than seeing the city as something to optimise, Smart Enough Cities place their need-based policy goals at the forefront, recognise the complexity of people and institutions, and think holistically about how to fulfil their needs. To bolster his arguments for Smart Enough Cities, Green explores how cities in the United States have used technology to create a livable city, a democratic city, a just city, a responsible city, and an innovative city.

Pointing to the optimism associated with the role of autonomous vehicles and intelligent traffic management systems in improving urban transportation, Green points out that these technologies could repeat the mistake of prioritising traffic efficiency over walkability and community vitality in cities. Rather than unreservedly embracing technology or outrightly rejecting them, Smart enough Cities stick to their planning goals while exploring opportunities offered by technology to achieve them. The city of Columbus in Ohio, recipient of a $40 million prize by the U.S. Department of Transportation for developing a smart transportation system, has a modest plan to improve mobility. Instead of subscribing to utopian visions of technology, it is focused on deploying solutions that address the city’s needs. The city has prioritised making transportation more accessible for all. For this, a unified payment card has been introduced since some residents lacked access to bank accounts and credit cards, a streamlined app was developed that unifies every transportation system in the city, and Wi-Fi access was improved in marginalised neighbourhoods. In its approach, Columbus demonstrates two attributes key to fostering Smart Enough Cities. First, cities need to have a clear policy agenda before deploying technology, and second, a research process that focuses on people rather than technology. The best way to avoid techno solutionism would be to learn what barriers and challenges people actually face.

To address today’s challenges of civic engagement and democracy, city governments and technologists have proposed several technologies to make politics and governance simpler and efficient. These include numerous technologies: online platforms, social networks and 311 apps, named after the phone number used in many cities in the United States to access non-emergency municipal services. Green points out that 311 apps may make it easy to notify the government about a broken streetlight, but they do little to empower residents or generate deeper community ties. Further, the public might have a new tool to inform municipal operations, but the tool is employed within the framework of traditional relationships between governments and those governed. The governed obtain services from the government without being empowered with greater agency over decision making or public priorities. Green argues that it is precisely because 311 apps are compatible with existing incentives and institutional constraints – rather than being revolutionary – that governments have eagerly adopted them. The technological focus on making civic engagement efficient creates systemic blindness to the responsibility of the government to cultivate real channels of meaningful dialogue and dissent. Green cites the example of Boston, which has come up with Community PlanIt – an online multiplayer game that facilitates engagement, deliberation and decision making within communities. Contrary to the approach often taken by purveyors of technology—of eliminating inefficiencies—the developers of Community PlanIt highlight the importance of ‘meaningful inefficiencies’, which enable citizens to share in a give and take of experience and increase their range and perception of meanings with each other.

Police departments in many cities in the United States have adopted predictive policing software in a bid to be innovative and race-neutral. On the contrary, by providing a layer of apparent neutrality, predictive policing algorithms justify and exacerbate discriminatory inequities, and police practises. Pointing to the Chicago Police Department as an example, Green highlights that in the hands of the police, even algorithms intended for unbiased and non-punitive purposes are likely to be warped and misused. The city police initially used algorithms to identify people most likely to be involved in gun violence. Although the original stated intention of the technology was to prevent violence, it has primarily been used as a surveillance tool that disproportionately targets people of colour.

Green then goes on to explore the growing trend of data collection by public and private entities and its implications on privacy, surveillance, and algorithmic transparency. In a bid to bridge the digital divide in the city, in 2016, New York introduced LinkNYC, a program to provide free public Wi-Fi via internet-connected kiosks placed throughout the city. Though it appears to be a benevolent technical solution, under the surface, it is anything but. The kiosks are owned and operated by Sidewalk Labs, a subsidiary of Alphabet, which plans to pay for the initiative by collecting and monetising data about everyone who uses the service. LinkNYC kiosks are equipped with sensors that gather an enormous quantity of data about every device that connects to its service. Not just its location and operating system, but also its MAC address – a device’s unique identifier. Other than the legitimate concern of commodification of personal information by data brokers, widespread surveillance is equally worrisome, as governments and private entities are allowed to monitor every action, infer intimate details and create virtual profiles of citizens.

Green points out that it is not just increased data collection that threatens to create an undemocratic social contract in cities. Cities are increasingly using algorithms to inform core functions like policing and social services. Despite the seemingly sophisticated nature of these algorithms, they are neither foolproof nor neutral. Bias can arise both in the training data on which they rely and in how they are deployed. Municipal implementation of algorithms raises grave concerns for urban democracy since cities typically provide the public with little or no insight into how their algorithms were developed or how they work.

In many cases, algorithms are concealed because they are developed by private companies with a financial interest in secrecy. These new public-private relationships shift decision-making away from the public eye. As a result, governments may make consequential decisions about people without providing any transparency regarding how those decisions are made. Green points to the Kafkaesque example of Eric Loomis, who was given a six-year sentence by a court in Wisconsin. The judge used an algorithmic risk-assessment tool to conclude that Loomis was a high-risk individual, likely to re-offend. Since the algorithm behind the risk-assessment tool was a trade secret, Loomis was not permitted to assess how the algorithm made the prediction, and subsequently could not challenge his sentence.

One of the smart city’s most alluring features is its promise of innovation. However, the role and meaning of innovation are often misappropriated. Often, innovation is redefined to mean making something more technological. Consequently, traditional practices are devalued as being emblematic of the undesirable dumb city. Pointing to the examples of San Francisco and New York City, Green highlights that “the most important innovations occur on the ground rather than in the cloud”. Technological innovation in cities is primarily a matter not of adopting new technology, but of deploying technology in conjunction with social change and expertise. Municipal leaders in San Francisco and New York City have demonstrated how to deploy data to improve local governance – not by expecting data to magically optimise government or solve local issues, but by building relationships with departments, fostering best practises for maintaining and sharing data, and training city staff in how to use data to improve their operations.

Green’s key message is that we stop and think about implementing technology. What are we trying to achieve? If technology is the answer, then are we really asking the right questions? Therefore, cities need not be “smart” and blindly chase efficiency and connectivity. Instead, they need to be only “smart enough”, and ask the right questions to advance their social policy goals using technology.

The publication was first published by the authors under auspices of erstwhile Tandem Research.

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