“A Drama in Time”: How Data and Digital Tools are Transforming Cities and their Communities

Technological innovation and advances in information technology (IT) contribute to the accelerated pace of urban life in the United States and around the world. As hardware, software, and IT systems have become more sophisticated, they are called upon to meet challenges and opportunities of urbanization and its attendant growth in density of people, housing, transit, and commerce. Amid the justified excitement for the possibilities technology affords, scholars and practitioners should also maintain a people–centered approach to the development, implementation, and assessment of these new platforms. Enthusiasm for technological advancement must be balanced by careful attention to its direct and indirect effects on local communities.

Why cities? Cities are crucibles where stresses on the environment and social systems make them excellent testbeds for improving digital tools for decision support among officials, occupants, and business owners. City–level officials (mayors, city council representatives, agency leaders) are more immediately accountable to their constituents than officials in more remote jurisdictions (state or federal), and their decisions have the most near–term, immediate impact. ¹

Today over half the world's population lives in cities, a percentage projected to increase to two–thirds by 2050. ² Noting that the steepest growth in urbanization will occur in developing countries, the UN Department of Economic and Social Affairs urges that sustainable urbanization is key to successful development. Private funders such as the Rockefeller Foundation have recognized the need for “resilient cities” that can better prepare for and withstand chronic stresses and acute shocks. ³ The technology industry has framed initiatives around the concept of “smart cities,” used by companies like IBM, Cisco, and Microsoft, to sell software and services that improve management of urban infrastructure. Multi–stakeholder convenings, like Meeting of the Minds or the Smart Cities Innovation Summit, bring together city leaders with industry executives, advocacy organizations, and private donors to address growing urban needs. ⁴ The White House has launched its own Smart Cities Initiative, informed by a February 2016 PCAST report on “Technology and the Future of Cities,” ⁵ offering millions of dollars via Federal agencies (DOE, NSF, NIST) for urban infrastructure investments. ⁶ These investments will require reliable data, digital tools, and cyberinfrastructure.

“Big data” includes the large volume of structured and unstructured data, beyond the capability of general–purpose software tools to store and manage. Data may be generated from a variety of sources, and challenges to its effective use include its collection, curation, storage, analysis, and visualization, as well as concerns for individual privacy and security. The convergence of digital applications and infrastructure with an influx of population into cities has spawned the field of “urban informatics,” a promising area of interdisciplinary inquiry with rich opportunities for translation of insights into practice.

How might advances in digital technology apply in an urban context? For cities, data sources may be sorted into three categories, each with its own opportunities and cautions: •

Passive: Data collected from fixed sensors, such as those placed in roads, bridges, lampposts, and similar infrastructure, along with other devices in the Internet of Things (IoT).

Using empirical data to improve urban life is not new, only its volume, velocity, and variety have increased in recent years. ⁷ Today's tools are being integrated into traditional sectors with exciting results. I will discuss three broad application areas below—public services, environment and transportation, and civic engagement—and conclude with a few considerations and cautions when applying digital tools to urban concerns.

Public Services

A key responsibility of city leaders is to provide public services, such as emergency response, law enforcement, and adequate infrastructure. Harnessing data improves response times and efficiencies in all these areas.

IT advances have led to improved management of 911 calls and optimized placement of rescue vehicles by using GPS for fleet tracking and route planning. Ride–hailing service models have been proposed for those needing urgent care, as the patient can monitor the estimated arrival time, and, for those paying out–of–pocket, the service is far less expensive. Medicaid even pays for private transportation by car in some areas, and healthcare systems are creating partnerships with Uber and Lyft for scheduling rides to routine appointments, finding that access to reliable transportation reduces missed appointments by 10–51 percent. ⁸

But should Uber replace ambulances in case of real emergencies? Freelance drivers are not equipped to provide care, and lack of professional attention may delay appropriate diagnosis and treatment of life–threatening conditions. ⁹ A compromise solution is found in a pilot program being tested to deploy professional EMS workers and trained community volunteers simultaneously; United Rescue in Jersey City, NJ, follows such a model, which could be replicated elsewhere. ¹⁰

Effective digital tools promise to reduce the incidence and extent of urban fire by combining analysis of building code inspections and historical risk data. New York City and Atlanta, Georgia, ¹¹ have used such data to train predictive models, which has optimized staff time for inspections and reduced loss of property and life. These examples use recent IT advances to prevent hazardous situations, but computer algorithms were introduced already more than 40 years ago to improve fire response times and preparedness in New York City. ¹²

In the unglamorous world of infrastructure maintenance, platforms like SeeClickFix allow city occupants to report problems like potholes, graffiti, and streetlamp outages. ¹³ StreetBump.org crowdsources information about road conditions using data from smartphone accelerometers and GPS. Solid waste management initiatives in urban capitals around the world are using big data to improve collection. ¹⁴ The U.S. firm Bigbelly makes solar–powered trash compactors that use sensors and cloud computing to detect when cans are full and improve route management for trash collection. ¹⁵

Media and advocacy organizations have devoted attention to big data's influence on law enforcement. On the one hand, data can improve public safety through identifying crime trends or characteristics of likely offenders. On the other hand, such predictive analytics can lead to racial profiling (e.g., controversial tactics of “stop and frisk”) and systemic injustices from arrest through pre–trial detention, prosecution, and sentencing. The growth of technology in facial recognition and machine learning must also be approached cautiously. ¹⁶ Use of video surveillance will undoubtedly increase for public safety and disaster response. Video technology, combined with rapid advances in facial recognition, can potentially reduce human–hours required for criminal investigations but also present challenges to civil liberties and privacy rights.

Environment and Transportation

Data from fixed sensor networks or contributed by city occupants can be used to monitor a variety of environmental conditions. Air quality sensors, for example, can measure particulates and other pollution, and potentially be mapped on publicly available platforms; such capability is useful especially in developing regions like China, where urban air quality is poor and citizens may not trust government reports alone. ¹⁷ Combining data sources also yields insights on air quality under dynamic conditions, such as population movement into and out of urban centers during commute hours. ¹⁸ The combination of inexpensive measurement devices and online platforms for data collection can facilitate citizen science projects that crowdsource documentation of environmental hazards. For example, a technology–based citizen–engagement project monitored water quality in Flint, Michigan, during the 2014–2015 crisis, when house–level data improved media coverage and advocacy for local, state, and national action. ¹⁹

One source of pollution, not to mention lost productivity, increased aggravation, and wasted fuel, is poor urban traffic management. In a 2011 study, IBM researchers estimated that over 30 percent of traffic in the 20 international cities surveyed is due to drivers searching for parking. ²⁰ Crowdsourced data and its effective visualization promise to optimize transportation in private vehicles through use of ride–hailing platforms (reducing the number of drivers and cars), mapping algorithms like Google Maps or Waze, and a variety of dynamic parking solutions. ²¹

Civic Engagement

Data and the internet have contributed numerous improvements to civic transactions of government. Nonprofit organizations like Code for America and federal agencies like 18F have borrowed concepts and practices from the tech sector for the benefit of public service. Several major cities have created positions devoted to civic innovation and data. The Chief Data Officer, Chief Innovation Officer, Chief Resilience Officer, and similar roles all use data to improve local interactions between the city and its occupants. Some city offices are at the forefront of using urban informatics to improve city services, for example, the network of civic innovation offices of New Urban Mechanics begun in Boston and Philadelphia, or the New York City Mayor's Office of Data Analytics.

The open data movement, whose rise parallels that of other “open X” movements (open access, open science, and the like), makes public data accessible, machine–readable, and actionable. The United States and India were among the first countries to publish national data sets, and many more countries, states, and cities followed. ²² The availability of open data enables residents and interest groups to improve government transparency and accountability, but it can also serve a broader purpose, allowing citizens to take a greater stake in their own governance and provide a platform for building community and fostering bottom–up innovation. Regardless of whether a community hackathon or similar event around open data results in a new application, such occasions can provide a focus for neighbors to discuss issues they care about. And indeed the outcome or consequences of open data research, rather than the method per se, will lead more effectively to social change. ²³

Cautions, Considerations, and Future Trends

Along with the advances in big data and the algorithms that govern its use come concerns regarding their potential to exacerbate the digital divide. Some questions arise from disparities in access, others from lack of inclusion in the benefits or inequitable representation in the “raw” data upon which decisions are made. ²⁴

Interoperability challenges loom large. Even within a given city, information in databases may not be easily shared between or among departments, and difficulties are exacerbated across jurisdictional lines (e.g., city vs. county). Effective deployment of these tools is hindered by lack of integration between systems, as well as lack of completeness in the data. Data can be deceptively “objective,” yet omissions or gaps affect service delivery and resource allocation.

The financial cost of improving digital infrastructure cannot be underestimated, especially in perpetually strapped public organizations. Budgets must provide for upgrading equipment, software, and licenses; data storage, security, and management; and personnel to support IT infrastructure, cybersecurity, workforce training, and more.

Despite the improvements to urban life promised by digital applications, they are matched by potential threats to individual privacy and systemic security. Hacking took down Ukraine's electric power grid in December 2015 and ransomware temporarily crippled the ticketing functions in San Francisco's Municipal Transportation System (MUNI) in November 2016. ²⁵ The more cities rely on IoT and cyberinfrastructure, the more vigilant against attacks they must be.

With the growth of capacity in data collection must come the duty to manage it responsibly; this is a two–edged sword, as data can be used not only to promote transparency and accountability, even in documenting discrimination or prosecuting crimes, but also to carry out those crimes in the first place. ²⁶ With an incoming Presidential administration threatening to create registries of Muslims, abuse of mechanisms for data collection is not an idle concern.

Ultimately, effective use of big data to improve urban systems and quality of life comes down to human choices, not machines. People must make decisions in favor of equitable access, create conditions for data literacy, provide the tools and knowledge for effective crowdsourcing, and enable sufficient understanding to read, interpret, and act on results. “Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that's something only humans can provide.” ²⁷