Laura Bliss is CityLab’s West Coast bureau chief. She also writes MapLab, a biweekly newsletter about maps (subscribe here). Her work has appeared in The New York Times, The Atlantic, Sierra, GOOD, Los Angeles, and elsewhere, including in the book The Future of Transportation.
Since 2010, a slew of on-demand companies and technologies have managed to use consumer data to transform the commercial significance of urban living.
In 1964, scientists in the Galápagos Islands fed radio transmitters wrapped in chunks of food to a bunch of giant tortoises. As the animals slept, wandered, and mated, their behaviors pinged back to the research team’s receivers in the form of radio signals.
This early use of telemetry, or the transmission of computer information over long ranges, proved that biologists could observe, make inferences about, and even influence their subjects remotely. In her 2019 tome The Age of Surveillance Capitalism, the Harvard scholar Shoshanna Zuboff writes that the tortoise experiment was also a prelude for the kind of data-collection technology that has become ubiquitous in human society. And in the 2010s, it began to transform the shape of modern cities.
Today, as with the reptiles, we’re sometimes monitored for scientific purposes. Think of the fecal probes that MIT scientists sent into the bowls of Boston’s sewers to search for traces of opioid use. In some instances it is for government and law enforcement, as with streetlight cameras that count vehicles, scan license plates, or nab red-light runners. But the largest stage of telemetric technology has been for commerce. Our data as consumers and participants in daily life are not simply passively gathered: Consolidated, it has become the raw material for many of the products and services we buy.
It’s well known that Google, Facebook, Microsoft, and other information technology companies bottle up our digital exhaust while we’re using their products (and even while they’re just running in the background). Our clicks, keystrokes, and physical locations are aggregated as data points and smoothed into forecasts for our future choices, which turn into nudges towards certain outcomes. That might mean an online ad for the microwave you hovered over, an invitation to “like” a company’s Facebook page, or a coupon for a nearby retailer popping up on your phone. Over the past decade, telemetry has soared to new heights of power on the commercial web: Amazon has amassed 360-degree views of its “everything store” customers to guess our incomes, predict our desires, and charge us prices we’ll jump to pay.
That predictive architecture now shapes how we move through the physical world, too. Modern household lighting, kitchen appliances, personal vehicles, public streetlights, malls, and airports amass telemetric information about their human users and occupants, then use those insights of the crowd to tweak our habits and environments. A “smart” traffic intersection might give priority to city buses. A “smart” car might ramp up your insurance payments. A “smart” TSA scanner might help inspection agents target certain travelers. And a “smart” city? It might watch over and organize how its residents use public spaces, gathering data and sending nudges with aims of improving efficiency, safety, and public health.
The risks and benefits of using these technologies for urban planning and law enforcement are the subject of great debate, and they’re still revealing themselves in practice. But big data analytics have done more than cast a Big Brotherly shadow over urban space. They have also changed the significance of a basic element of what makes them urban: dense proximity.
Historically, one of the great economic benefits of urban life is having access to jobs, schooling, goods, and services without needing to travel very far. But digital platforms that aggregate consumer demand are making physical density less important. Uber and Airbnb, the killer apps of the 2010s, exemplify this change. Once upon a time, visitors needed to flock to quarters where a city’s supply of hotel accommodations and other tourist amenities were physically consolidated, usually downtown. If you needed a ride, you used to call the taxi company directly, or flag down one of the cabs that served that area.
Now we transmit our demands for trips and beds as data from wherever we are, rather than direct interactions that depend on physical nearness. Uber and Airbnb consolidate our requests with those of a sea of other users, set prices, offer us suppliers, and dispatch them to us (for more on this, see the technology analyst Ben Thompson’s aggregation theory). The apps are creating their own agglomerations of demand, networks that are held together via digital ligaments instead of actual proximity. Kevin Webb, a transportation data expert, points out that Amazon works the same way, building off the big-box store model that came before it: Instead of physically traveling to an area where you can buy tennis balls, shampoo, and a can of tomato paste at three different but close-together shops, its shopping algorithms mean that it can stash those items on a single warehouse shelf thousands of miles away.
What does this shift mean? On-demand platforms have made certain kinds of goods and services more convenient, affordable, and accessible for customers across the income, age, and race spectrums. New places and things opened up for new markets. But the less-desirable consequences of replacing physical marketplaces with digital bundles of demand have been major. As ride-hailing emerged, the taxi industry in most cities has been gutted; in many others, traffic congestion has spiked and transit ridership has declined. Thanks to online short-term rentals, traditional hotels have seen a declining share of travelers opting for their wares and neighborhood housing shortages have been exacerbated by hosts who rent to Airbnb guests rather than full-time tenants. In some cases, once-residential neighborhoods have been emptied of locals and turned into streets of rentable ghost hotels.
As those effects manifested in cities from Tuscaloosa to San Francisco over the 2010s, critics blamed these upstart industries for wreaking havoc on traffic planning, housing prices, and local labor markets. But a subtler impact may be just as important: They altered a key ingredient of what makes an urban economy. The 2010s were the decade the city became an App Store: an online marketplace where our choices were closely tracked, where that data became part of the products we were using, and where digital clusters of activity displaced real-world transactions. Yes, we still go downtown for drinks, meals, and shopping experiences. But, more and more, we live in cities of the cloud.