As the Chorus of Dumb City Advocates Increases, How Do We Define the Truly Smart City?
Source: Harvard Kennedy School | BY STEPHEN GOLDSMITH • SEPTEMBER 16, 2021
Recently, the Boston Globe published a provocative interview with Shannon Mattern, who asserted that smart cities are, in fact, dumb. Mattern, a professor of anthropology at The New School for Social Research in New York, joins the calls of several others who are advocating that we throttle the smart city enthusiasm.
In a more nuanced opinion piece, Shoshanna Saxe, an assistant professor of civil and mineral engineering at the University of Toronto, advocated in the New York Times that often, ‘dumb’ cities will do better than smart ones, setting up a false choice between people and technology. According to Saxe, “the parks, public spaces, neighborhood communities, education opportunities — are made and populated by people, not technology. Tech has a place in cities, but that place is not everywhere.”
Clearly, in writing this response, this author has a specific point of view—this response, after all, is posted on a site called Data-Smart City Solutions, and this author manages a program for city chief data officers. While the critics of smart cities raise legitimate questions and concerns, they also raise certain strawmen – the failed Sidewalk Labs effort in Toronto being their highest profile.
First, we need to deal with the definitional problem—there is no clear definition of a smart city. Years ago, as an elected prosecutor, my team in the district attorney’s office implemented what were then the country’s most advanced digital tools to increase the child support we collected from noncustodial parents and distributed to struggling mothers. Collections surged from $900,000 to thirty-eight million dollars annually; to me that was a harbinger of smart city efforts. When, as mayor of Indianapolis, we used digital geographic information systems to identify the city’s most neglected neighborhoods, along with their assets and needs, that struck me as a smart idea. Especially since these analytic visualizations sparked and provided the foundation for community partnerships, a substantial investment in services, and hundreds of millions of dollars in infrastructure.
And, when I worked as Mike Bloomberg’s deputy mayor in New York City, we took the first steps to create a data analytics center that would infuse data-driven decision making into a wide array of areas, from inspections to tax collections, ensuring safer restaurants and increasing tax revenue. Bloomberg’s Deputy Mayor of Social Services Linda Gibbs introduced one of the country’s most advanced uses of digital tools, which simplified and integrated access to social services for those in need. To me, all of these are examples of a smart city; technology was implemented at the local government level to improve the lives and experiences of residents.
To move away from the strawmen—the arguments that a city can’t pay attention concurrently to people, equity, and technology, or the one that holds up Sidewalk Labs’ ambitious and now largely abandoned effort to develop a smart city enclave in Toronto (which was much more a commercial undertaking than a city undertaking), we need a definition. While no simple task, I propose that a city administration could consider itself smart to the extent it adopts these ten criteria.
1. Uses data to deliver city services based on where and when they can do the most good.
Most cities still operate on routines. For example, in these routines a call center receives a request for service; an operator logs it into a system, which eventually leads to crew being dispatched. But what if the traditional routine reinforced unequitable service delivery and dispatch? In Baltimore, an analysis of 311-reported cleaning work identified that this process resulted in geographical inequities in the way sanitation crews were being deployed. With this data, the Department of Public Works implemented a new sanitation strategy that focused on “clusters,” which allowed the crews to be more efficient and insure that overlooked communities received better services. A smart city uses data to determine priority, identify systemic problems, and understand what caused the issue. In every area of government there are outliers and “frequent flyers,” and a truly smart city will determine the causes of those frequent concerns and try to solve the underlying problem.
2. Creates digital platforms that allow it to use IoT data to improve the way it builds, maintains and uses physical infrastructure.
A smart city builds digital infrastructure that enables the integration of Internet of Things (IoT) data to deliver better, and safer, cities. It uses these digital platforms to better construct, monitor, and maintain infrastructure. Thanks to smart sensor technology, a bridge in need of attention sends a signal long before it collapses; a neighborhood with dangerous particulates in the air sends an alarm to public health officials. Mobility officials can see – in real time – curb usage by type: delivery vehicle, car idling, or scooter parking, and adjust the allowed usage and pricing to address demand and congestion. A smart city is not defined by the amount of its IoT data but rather its use; how it analyzes and uses the data to improve the quality of life and safety. Further examples of smart infrastructure technology can be found in Building Back Better with Intelligent Infrastructure.
3. Makes public employees smarter in their work.
In too many cities public employees are stymied by narrow job descriptions and outdated tools. In a smart city, all these dedicated public employees will be given the training, tools and technology necessary to improve their work, and therefore improve the city at large. Smart cities can also use machine learning to resolve simple requests, thereby freeing employees so they can address more complex problems. For example, machine learning can handle a large number of 311 calls, increasing the responsiveness of operators to calls that need more research.
4. Enhances the way it listens to and involves the public.
A smart city involves the community in deeper and more comprehensive ways than before. It will expand the definition of community meeting to include digital meetings and virtual design charettes. It will use anonymous sentiment mining to understand what specific communities think about an important issue. Recently, we participated with the Robert Wood Johnson Foundation on a project around vaccine hesitancy. City officials wanted to better understand the concerns that certain communities had around COVID-19 vaccines. Using anonymized social media data, city officials in the 18 cities across the U.S. were able to understand and address the hesitancy that many residents had, using the concerns that the residents themselves publicly shared and discussed on online platforms. The social media data revealed issues that the mayors could immediately…
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