Where Code Meets Concrete | Urban Omnibus
Where Code Meets Concrete Urban Omnibus


Photogrammetric rendering from Without Friction by Timo Bredenberg. Image courtesy of the artist.

“Imagine: You walk out of your luxury apartment building, toward your waiting Uber, when a drone drops from the sky and deposits an iced Americano in your hand.” A few years ago, on a tour of one of the world’s premier urban technology firms, an eager guide offered our group a glimpse of the good life he and his elite team were helping to program. And they hoped we would share their vision for an urban lifestyle of discreetly luxurious conveniences and seamless connections: a world that knows our preferences, anticipates our desires, and frictionlessly adjusts itself to accommodate them. The “coffee drone” was apparently an aspirational use case toward which many of the world’s most talented technologists were applying their skill and vision. IBM actually patented one in 2015, and more recently, Alphabet’s (née Google’s) Wing drone delivery service has successfully tested coffee dispatch in Canberra, Australia.

Municipalities deploying new, networked urban technologies and urban data analytics often justify their efforts by promising the fast, efficient, barrier- or seam-free delivery of goods and services. Civic entrepreneurs have also pitched smart urban systems as a means of streamlining and strengthening the provision of crucial services like transit and employment, care and security. It’s doubtful that optimized libation logistics are anyone’s idea of peak networked (sub-) urban living. Yet, as I’ve discovered in nearly a decade of researching and writing about digital infrastructures, data-driven urbanism, and “smart cities,” similar end goals — efficiency, seamless connectivity, predictive responsiveness — commonly infuse all of these smart city applications and use cases, both those rooted in luxury consumerism and those addressing common resources and social welfare.

Police leaders across the globe are deploying a constellation of surveillance technologies, criminal databases, and predictive algorithms with the goal of portending and preventing crime. Transit operators cross-reference riders’ geolocation data with vehicle sensor data in order to deploy vehicles precisely where and when they’re needed. And administrators in many city halls aim to fuse all their available urban data feeds in order to achieve the immediacy and certainty of what I’ve described elsewhere as dashboard governance.

Smart on the Ground

New York’s Police Department, Department of Finance, Department of Information Technology and Telecommunications (DOITT), and the Mayor’s Office have all partnered with companies including IBM, Microsoft, and Peter Thiel’s Palantir to develop data analytics systems, facial recognition technology, and surveillance apparatuses — all of which promise to make the maintenance of law and order more impartial, efficient, and unobtrusive. DOITT also scouted out an opportunity to provide seamless internet connectivity and efficient access to information, other key concerns in smart urbanism. They contracted with CityBridge — a partnership involving Alphabet’s Intersection, telecom equipment maker Qualcomm, and urban screen designer CIVIQ Smartscapes — to replace its old payphones with new networked kiosks that would (purportedly) provide free municipal Wi-Fi, help disenfranchised populations bridge the “digital divide,” and generate advertising revenue. (The LinkNYC program has been under scrutiny because of its surveillance and data-harvesting capacities.)

Independent entrepreneurs and civic tech developers are drawing on the city’s open data, or collecting their own, to develop new urban technologies — apps, platforms, and gadgets — that will ideally be adopted by, or perhaps sold to, the city. And larger research collectives — encompassing the city’s educational and cultural institutions and health facilities, for example — are proposing their own smart systems. As I reported last year, an interdisciplinary team of New York health professionals, decision scientists, urban planners, and data analysts planned to collect exhaustive personal data from a few thousand New Yorkers, use that data to “quantify the human condition,” and then transpose that formula into an algorithmic language for urban design. Measurements of human health would seamlessly translate into health-generating neighborhood plans.

Similar visions manifest in microcosm at Hudson Yards. The developers of this mega-project on Manhattan’s far west side recently disclosed that they’ve collaborated with Alphabet’s Intersection, AT&T, Verizon, and other vendors to implement biometric security systems that expedite building access (and, incidentally, location tracking) — and to create an app for residents that both supplants unwieldy door keys (such a bother!) and unlocks various local amenities. Related Properties’ Jay Cross, one of the property’s developers, said that management harvests data from tenants and visitors “for the purposes of allowing us to make Hudson Yards function better.” By “better” he means more efficient, more predictive and predictable, more compliant, more profitable.

Such “betterment” requires that more digital gadgets and data are “embedded into” and “layered atop” our physical metropoles. Sidewalk Labs, Alphabet’s urban tech division, which began its work in Hudson Yards before shifting its attention to Toronto, has portrayed its sensor networks, mapping platforms, public interfaces, and modeling software as an integrated “digital layer” discreetly underpinning the material city and its inhabitants’ urbane lifestyles. “Embedding” and “layering,” and other such verbs populating tech firms’ and real estate developers’ promotional copy, conjure up images of harmonic integration. Smart technologies will recede into the background, creating fluid efficiencies, silently orchestrating operations, unobtrusively nudging us toward the most frictionless pathways and self-actualizing behaviors. It’s the dream of ubiquitous computing — which its mastermind, Mark Weiser, envisioned as “calm,” or unobtrusive, technology — realized at the scale of the city.

The Seams of Urban Tech

In reality, however, cameras, sensors, antennae, algorithms, and other urban technologies often fail to meld with the material urban landscape and its legacy technologies: rusty tracks and ancient signaling systems, incompatible data models and protocols, lumbering bureaucracies and laboring bodies accustomed to particular modes of operation, marginalized communities already subject to excessive monitoring and wary of further attempts to “optimize” their neighborhoods. Where smart, supposedly seamless technologies interface with these old-school forces, “embeds” and “layers” are often experienced as obtrusive intrusions, ruptures, or frictions. Even in brand-new “cities from scratch,” built tabula rasa to reflect the logics of networked technologies, ruptures still commonly arise in the form of labor disputes, or in debates over financing, human rights, public process, and data management.

However purportedly user-friendly and foolproof their designs, urban smart technologies can still be exploited or misused by their handlers, overthrown or abused by their targets, foiled by the elements, or soiled by the city’s non-human inhabitants. Squirrels sometimes like to munch on fiber-optic cables. Floods and extreme weather events, less extraordinary in the age of climate crisis, create inhospitable environments for power-dependent infrastructures. Even sturdy LinkNYC kiosks can’t withstand the impact of bricks thrown by enraged New Yorkers (whose hostility is perhaps rooted in fear of encroaching surveillance, outrage over Alphabet’s expanding urban footprint, or some other smart city resentment).

While the urban elite commonly know how to build up legal and technological protections to exempt themselves from meddlesome monitoring, some marginalized populations also develop improvisatory hacks and ad hoc defenses from exploitative digital tracking and targeting; their tactics range from blocking security cameras, to building their own communication tools and networks, to avoiding online activity altogether. Meanwhile, the authorized users of official urban technologies engaged in that tracking and targeting often know how to exploit their gadgets’ weaknesses — to turn the algorithmic logic against itself. Police body cams and screening algorithms and motion sensors — all touted as reliable, impartial means of completing tasks prone to human error — are embedded with a particular logic and ideology that directs their deployment, and can easily be applied toward political ends.

Such acts of misuse, abuse, exploitation, and improvisation — from munching and flooding to evading and manipulating — generate frictions in smart technology’s deployment. And these actions are themselves often desperate responses to the frictions and fears that arise when cameras, sensors, and algorithmic systems start invading public housing and street corners — when smart tech is deployed in incompatible terrains.

The luster of seamlessness is wearing off. While designers and planners have until recently sought to smooth away such disruptions, we’re now witnessing within these same professions a growing acceptance, even in some cases an enthusiastic pursuit, of seams, frictions, and what Eric Gordon and Stephen Walter call “meaningful inefficiencies.” The argument is that by planning for productive frictions, we can de-obfuscate and de-fetishize “black-boxed” technologies and smart urban environments. And we can return agency to their users and inhabitants, who can then engage with the city and its technologies more thoughtfully and critically — and on their own terms, rather than those programmed into the urban operating system.

Digital Frictions

Many of the blue-chip, built-from-scratch smart cities — from Songdo, South Korea, to Masdar, UAE, and now, Saudi Arabia’s Neom — have proven themselves to be more mirages than municipal miracles. Scholars and policy makers are looking instead to “actually existing” smart cities, where smartness is often kludged and stapled onto, or stuffed into, an extant urban ecosystem. Arriving on the heels of the opening of Hudson Yards, and the first, disillusioning phase of Sidewalk Toronto’s development, this series focuses on digital frictions both intentional and accidental. Over the next few months we’ll examine those points of abrasion in New York where code meets concrete, and where algorithms encounter forms of urban intelligence that aren’t merely “artificial.”

While the smart city is frequently celebrated or critiqued from a 30,000-foot view, we’ll instead situate ourselves at ground level to ask: How do particular sites and situations of digital friction create both challenges and opportunities for design, planning, and daily living in New York City (and elsewhere)? We’ll acknowledge communities whose interests and legacies are commonly marginalized in “smart” plans, and we’ll explore sites of resistance — by humans, by machines, by the city itself — against virtualization and optimization.

Our contributors — design scholars and tech analysts, architects and librarians, critical cartographers and infrastructure artists, community network activists and documentarians of neighborhood institutions — will launch their individual explorations from their own material objects of interest, whether a data set or a door lock or a navigational app. They’ll consider how the design and deployment of these objects at various scales — at the urban and architectural scales, in relation to the human body, or distributed across vast logistical networks — generate illuminating tensions that prompt us to consider design values other than efficiency and convenience. And they encourage us to imagine how we can design digital urban systems that more responsibly and productively integrate with existing networks and place-based intelligences.

Ultimately, generative frictions can make for a much smarter, more inclusive, more vibrant city than those hypothetical smart cities composed of seamlessly integrated technologies calibrated for optimal efficiency. We’ll find that, sometimes, the inconvenience of that two-block walk to the coffee shop is worth it — particularly if it gives us an opportunity to engage with our neighbors along the way, to minimize our carbon imprint, and to avoid the surveillant eyes of a drone. Sometimes, we should maybe just make our own coffee — and while we’re at it, our own community networks and privacy-oriented platforms and productively inefficient building technologies. We aim to encourage urbanists and those working adjacent to urban technology — planners and policy makers, designers and data analysts, civic tech supporters and digital rights activists — to recognize the risks and rewards of planning for or against urban digital frictions, and to consider how a more “seamful” vision of a networked New York might allow us to blend the best of digital and analog urban intelligences.

Shannon Mattern is a Professor of Anthropology at The New School for Social Research. Her writing and teaching focus on media architectures, urban data, and information infrastructures. She has written books about libraries, maps, and the history of urban intelligence, and she contributes a long-form column to Places Journal. You can find her at wordsinspace.net.

The views expressed here are those of the authors only and do not reflect the position of The Architectural League of New York.



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