Why Data Alone Won’t Save Cities
Over the last few weeks, I’ve been working on a larger article that connects my views on climate change to cities and urban planning.
I subscribe to the notion that the design of our cities is the driving force behind our choices and behaviors. Although I’m still working on a thesis to summarize my views on cities and climate change, my general hypothesis is this:
If our behaviors control how humanity impacts climate change, then our cities are the first and last battleground for defeating the global climate crisis.
In the process of researching, learning, and collecting information, I’ve had trouble segmenting different areas on the topic of urban planning, climate science, and economics. I often found myself following dead ends or tracking loosely relevant ideas. To help with that distraction, I’ve started to write smaller segments about specific aspects of my viewpoints that may help me finish the larger piece.
One of the topics I’ve been reviewing is the concept of data collection and smart cities. I’ve been looking at data and its role in our “city of the future” conceptualizations. It goes without saying that one of the most high-profile examples of smart cities is the Waterfront Toronto + Sidewalk Labs project.
Rise and Fall of Quayside
Quayside is the first “internet-up smart city” designed by Sidewalk Labs (SWL), a subsidiary of Alphabet. In 2017, SWL partnered with the Canadian Government, drawing high praise from Trudeau and the media as a “community like none other,” deploying embedded technology (sensors and cameras) to usher in a new era of urban efficiency.
While it was clear Quayside would be the first neighborhood of its kind, many privacy experts and civic leaders opposed the project from the onset, citing considerations for privacy issues and civil liberties violations. It’s true that even with the former Privacy Commissioner of Ontario Ann Cavoukian on board, the project faced an insurmountable political challenge.
In the end, even with policies and systems in place to limit the capture of personally-identifiable data, entrusting a single private entity to own the data of an entire city and its people was too large a hurdle. SWL’s initial willingness to de-identify data at the source was casually overlooked once an urban data trust was established, leaving de-personalization of data up to the vendors providing the IT solutions. With growing economic fallout from Covid-19 and fierce political aversion, the Quayside project was abandoned in 2020.
What does this mean for an Internet-first City of the Future?
The promise and public excitement around Quayside were not solely based on the data collection. The project had ambitious and admirable goals that included:
creating an inclusive community for all income levels
acting as a test-bed for Canadian innovation in sustainable technologies and processes
creating a climate-neutral city
becoming a standard for a new concept of smart, connected neighborhoods for future developments
It aimed to deploy bleeding edge technologies in software, manufacturing, logistics, planning, and design, including innovations like:
construction (sustainable materials, prefab/modular construction techniques, flexible floor plans to accommodate different uses)
energy (clean energy such as solar and geothermal, heated sidewalks and raincoats for buildings)
transit (underground logistics infrastructure for mail, packages, and trash, interconnected mass-transit system to reduce dependency on cars, self-driving cars where needed, coordinated traffic signals, adjusted parking rates
technology (data monitoring using sensors and cameras to capture real-time use of public spaces, and predict movement patterns across all transit types)
The truth is, Quayside is just a concept, designed and built in a vacuum. While a data-driven city that optimizes our every move may sound like an idyllic look into the future for any tech startup, its practical use as a standard for future smart city planning is filled with holes.
Quayside is just a concept, designed and built in a vacuum.
There are 4 primary concerns I had about the Quayside project and why their new plan to divide its grand vision into separate parts may be the right approach moving forward.
1. Infrastructure
Any software developer or product designer knows that starting from scratch is always easier than working in an existing codebase or a layered artboard with limited documentation. With Quayside, the same is true. The solutions developed in Quayside are not separated into phases of implementation, they’re all integrated cleanly from the ground up with no dependencies, no need for refactoring, no sloppy code or unlabeled layers. Applying an Internet-up approach to old cities like New York City, San Francisco, Houston, and virtually any coastal city would be next to impossible.
2. Urban Planning
This is a larger topic that I’m still learning about, but my general viewpoint is that no comprehensive urban redevelopment plan cannot be done in isolation. Redeveloping roads changes routes. Adding fiber-optic cables requires underground infrastructure that extends outside the immediate city. The same thing goes with underground conduit for clean energy generated from solar farms, wind farms, or even geothermal. Moreover, the solution to create a carbon-neutral city doesn’t go far enough. Each city has far-reaching implications on the cities and lands surrounding it, which SWL did not have control over. This has critical implications on how mass transit will be developed, what neighborhoods it will impact, and how it will organize neighborhoods to make access to the city’s resources more equitable. It also does not take into account how to redesign older communities to reduce sprawl and consolidate resources to major centers, eliminating the need for mega-highways and higher VMT per family per year (vehicle miles traveled).
3. Data
Using sensors and cameras to track and monitor citizens and collect data within a new city already drew red flags in a urban block, imagine deploying surveillance technologies in existing cities with complicated political structures and rapidly-mobilizing activist groups. Information should be used non-invasively, with a federal policy to always de-personalize the data at the source to remove privacy concerns and ban the activation of personalized data for profit. For now, the blind data we collect should focus on how our policymakers and planners can serve their citizens by creating more walkable cities that are interconnected and reduce sprawl. It should focus on how to efficiently use tax dollars to introduce more mass transit lines to weave a layer of interconnectedness between neighborhood enclaves, create more equitable housing, and increase our connection to greenery and each other through public spaces accessible by foot and bike.
4. Policy
Quayside was a solution to the wrong problem. The solution needs to address issues with inequality, public health, social well-being, and environmental health in established cities. The outcomes of Quayside should have focused on collecting anecdotal evidence for the standardization of a new urban plan that reduces cars on roads and eliminates non-walkable corridors to test the hypothesis that this new plan will result in an overall improved sense of community, economic growth, and social well-being. Cities are living entities that thrive on random serendipitous collisions and interactions. Hyper-optimizing a city for efficiency removes the humanity and random accidents that define the character of a place. The nature of community is just as important as the design of a city and policy is a reflection of that — the people.
I’m excited about several aspects of Sidewalk Labs and other startups that are working to address the gaps in our understanding of cities.
Delve - Delve uses generative design to help urban development teams design better cities. Although the cities within a city are important, so are the intangible human factors. This is something that Delve will need to look into incorporating to make truly equitable cities.
Replica - Replica captures de-identified location data via cell phones to map movement patterns throughout the city. Aggregated mobile location data is combined with demographic data from public sources to create identic synthetic populations and generated public transit maps that planners can use to plan large-scale transportation projects.
UrbanFootprint - Founded by Peter Calthorpe, UrbanFootprint has created a system that collects data to help policymakers and other stakeholders make informed decisions across several key layers of land, including comprehensive, context-rich data about the urban and natural landscape paired with targeted insights that measure risk and opportunity to prioritize investments.
The future may be data-driven, but it’s also humanity-focused, and the companies looking to make an impact on our cities of the future shouldn’t lose sight of what we’re solving and for whom we’re solving it.