DL Seminar | Smart Cities/Digital Neighborhoods: Privacy, Equity, and Adoption of Urban Technologies
Updated: Jan 8, 2019
By Oluseyi Sonaiya | Masters Student | Cornell Tech
The September 20, 2018 edition of the Digital Life Seminar series at Cornell Tech welcomed Prof. Eran Toch, co-director of the Interacting with Technology (IWiT) Lab at the Department of Industrial Engineering of Tel Aviv University, to speak on Smart Cities and the relationships between neighborhoods, communities, and municipal digital technology initiatives. Over the course of his hour-long talk, Prof. Toch explored the definition of a “smart city,” the taxonomy of digital cities, and examined the discourses around them from the perspectives of technology companies, municipal governments, and the citizens themselves. He then zoomed in on how we understand residents in smart cities and their geographic variance in forms and frequencies of engagement, before closing with thoughts on the futures of digital cities.
The rhetoric of “Smart Cities” is everywhere, a reality that Prof. Toch wryly highlighted with numerous ready examples of mayors of major metropolises posed in photo opportunities next to some piece of urban tech or speaking passionately about some initiative. There is also big money in smart cities, as large corporations make significant infrastructural investments in exchange for permissive data access rights, offsetting costs that would ordinarily fall to local governments. There is widespread belief that urban and municipal technology will yield order of magnitude shifts in the way residents live their daily lives, with massive profits accruing to the firms that are correctly positioned to reap the benefits—a multi-sided win.
But first, what are Smart Cities?
Revealing that he preferred the label, “digital cities,” Prof. Toch defined them along two axes: the one comprising technological approaches that focus on digitization and deployment of information and communication technologies in urban spaces; and the other, economic interventions that cultivate the high-tech sector and as a result reap significant returns. Speaking more generally, those two axes define the possibility space for, “cities that are embedded with digital technology, in a way that can significantly change the way the city is used.”
Smart city initiatives take on many different forms. In Rio de Janeiro, the Operations Center performs traffic and security surveillance, weather forecasting, and monitoring for electricity and gas provides. Singapore’s Smart Nation Projects are a collection of distinct digital integrations, including the National Steps Challenge in which the city state gave some 800,000 step trackers to citizens and publicized neighborhood challenges as a means of promoting health and general wellbeing. Some initiatives are audacious, such as Sidewalk Toronto, a Google Sidewalk Labs agreement with the city to develop a 12-acre waterfront real estate parcel into a “city built from the Internet up,” merging physical and digital realms.
These large, governmental, public-private partnerships illustrate a range of approaches across the globe with government participation. In the United States, however, Dr. Toch observes that smart city efforts tend to be more private-based and market-centric, offering the examples of Uber, Lyft, TaskRabbit, and Postmates as firms that are changing the way the city is inhabited, navigated and lived in.
Broadly, smart city initiatives can be classified according to their organizational architecture, operational domains (transportation, energy, waste, emergency services), and technological levels (hardware infrastructure, communications, software infrastructure, data, and/or applications).
Top-down applications are created by the municipality itself, such as New York City’s Shot Spotter system that employs microphones to identify gunshots in neighborhoods, or Tel Aviv systems that track social media to highlight references to the city and bring potential citizen discourse to the attention of administrators. Commercial applications, such as Uber or Waze, provide benefits to city-based customers, but also serve up learning data to the city—and the corporations that operate them. Bottom-up applications, on the other hand, are built by the citizens themselves to organize organic and civic activities, from hiking groups to peer-to-peer mesh networks that provide connectivity where commercial vendors have not yet found financial viability.
The distribution across these organizational approaches is not uniform; smart city technologies are primarily used by governments, with both individual and aggregate citizen benefit in mind. This does raise questions about privacy, especially when large amounts of potentially de-anonymizing data are collected, particularly because the city traditionally offers a greater degree of privacy in public than a small town or village: the teeming masses of people simply don’t monitor each other as much or as closely.
Related to privacy is the question of whether smart cities drive increases in equality or inequality for citizens. Prof. Toch gave the example of a Massachusetts Institute of Technology project to use mobile phone accelerometer data to identify pothole locations. The expectation as that less affluent regions of the city would be better represented, as they received less road maintenance attention, but the actual data correlated to the nice parts of town. Upon further investigation, it turned out that predominantly affluent users installed the app, and as such identified potholes in the areas where they drove, i.e. their own neighborhoods.
This realization led to a line of inquiry that informed Prof. Toch’s own research: different populations have different accesses to technology, and commercial and sometimes even municipal services are often either not offered or are more expensive in marginalized communities. What is the relationship between urban social structures and residents’ adoption of digital urban services and attitudes toward them? What is the relation between privacy attitudes and the adoption of urban digital tech? What are the characteristics of (in)equality in the urban digital divide?
The hypothesis of Prof. Toch’s working group was that neighborhoods, and not just demographics, would have a major impact on adoption, and this proved correct.
To study these questions, the researchers from Prof. Toch’s IWiT Lab examined usage data for a suite of resident-facing digital services developed by the city of Tel Aviv, most packaged under the “Digi-Tel” service umbrella (which helped win Best Smart City in the World at the Smart City Expo World Congress 2014, in Barcelona). The team discovered that affluence was a strong predictor of digital service use. For every quartile increase in household wealth, Digi-Tel service use increased about 20%, and yielded an even stronger prediction effect for frequency of use.
All populations across the city use smartphones to a high degree, Prof. Toch said, but less affluent populations use computers significantly less, so making digital applications available primarily for computers has a gating effect.
Neighborhoods matter, even above demographics. They play an important part in determining technological literacy, and predict privacy concerns, albeit non-linearly. Tel Aviv City Center residents had about 30% more privacy concern than wealthier residents of Bavli, or poorer residents of Ajami or Shapira.
Adoption of urban digital services relies on their perceived usefulness, resident digital literacy, and privacy attitudes. While privacy attitudes affect adoption, this is mitigated by behavior. Younger, more college-educated residents had higher generic privacy concern levels, but when presented with specific scenarios—how would you feel about your information being passed to the police in the case of a crime?—the various neighborhoods evened out.
The lesson, then, is perhaps not to think about smart cities or municipalities, but about smart neighborhoods—and to build and promote services not along municipal lines, but cultural ones. The benefits of urban digital technology can be significant, but ignoring the nuances of neighborhood character and concerns can turn residents off from accessing valuable and available services.