The state’s management of racial categories is analogous to the management of highways or ports or telecommunication: racist ideological and material practices are infrastructure that needs to be updated, upgraded, and modernized periodically.
—Ruth Wilson Gilmore and Craig Gilmore, Restating the Obvious
“The most effective technology,” observes urban theorist Nigel Thrift, “is what becomes adopted as infrastructure.” Writer Tsutomu Nihei takes this assertion to the extreme in a manga where urban governance is fully automated, performed by a computer program designed to optimize the city’s core functions. The program ultimately decided that in maximizing the use of city resources, it was best to remove humans from the equation. It achieved this through massive machines that were originally designed to manage infrastructure. The machines were reprogrammed to banish humans from the urban core, which they achieved by digging an artificial canyon, forcing people into the canyon, and then encasing them with an impenetrable dome called the megastructure. The human underground was also patrolled by drones that could instantly materialize almost anywhere through futuristic three-dimensional printers located across the territory.
The criminal justice system’s burgeoning network of smart machines makes Nihei’s vision appear less and less fictional. The past decade and a half has watched a mounting assortment of smart cameras, monitors, and sensors make their way into urban infrastructure. What is more, many cities have taken to building digital infrastructures exclusively for criminalized populations. These systems operate according to what geographers Clyde Woods and Katherine McKittrick call plantation logics, as their objective is “physically fencing [places] off, and condemning their sociospatial difference.” Contrary to Nihei’s account, the spread of the carceral state’s digital architecture is not the result of unchecked automation. One of the first major waves of smart infrastructure was prompted by national security initiatives at the beginning of the War on Terror. At this point, the Department of Homeland Security (DHS) worked with the private sector to fortify areas of high economic importance. But eventually, urban police departments became vectors of smart securitization, which resulted in ensembles of smart machines slowly materializing in areas of low economic importance for very distinct purposes.
The idea that digital computers could manage urban processes traces back to the 1960s. During the decade, companies like Control Corporation, General Electric, North Electric Company, and Westinghouse began to build minicomputer-based systems that could autonomously and remotely regulate energy grids. It was these industrial powerhouses that planted seeds for the notion that city infrastructure could be administered by dead labor. The idea that these machines could administer poor minorities was conjured by the informational powerhouses that rose toward the end of the century. It is worth noting that this idea formed during a time when public infrastructure development, ownership, and operation in cities had become driven heavily by the private sector. The carceral state’s infrastructure was not immune to this, as it became increasingly common for prison construction to be financed through lease revenue bonds and exchange-traded funds bundled into larger public projects. By the time cities began exploring ways to modernize public safety infrastructures, IT companies had also become formidable actors in the infrastructure sector. The firms stridently introduced their own vision of urban society anchored in the Internet of Things (IoT), or networks of smart machines that autonomously communicate and interact with each other. Giants like the International Data Corporation, IBM, Motorola Solutions, and Siemens began to work diligently to transfer as many public services and facilities as possible into their ecosystems of smart machines. In doing so, they offered a utopian vision to public officials of cities where economic transactions, energy provision, street lights, subway systems, traffic lights, and, eventually, criminal justice would be managed by machines talking to one another behind the scenes.
On one hand, smart urbanization has established previously undreamed of amenities for privileged “users” of urban space. Machines communicating across airports, public transportation systems, and mobile transportation platforms make travel between global cities increasingly frictionless for professional elites. Telematics systems connect businesses, consumers, and city officials into a global network of ceaseless interaction and exchange. But on the other hand, at the same time, smart infrastructures engender new forms of exclusion and enclosure. Cities have erected special architectures of surveillance around public housing, public schools, and street intersections. Small tech companies like MorphoTrak and Nomad Global Communications Solutions help police make mobile booking units that allow officers to identify, photograph, and fingerprint suspects while they are still in the street. Criminalized communities are thus finding themselves slowly enveloped by the carceral state’s infrastructural landscape.
The ceaseless documentation, analysis, spatiotemporal prediction, online monitoring, and surveillance of criminalized neighborhoods is what one gets when information capital penetrates the criminal justice apparatus. While the industrial capitalists no longer find these areas exploitable, the information capitalists do. For three decades, IT companies have proposed a steady stream of new technologies they claim will make managing high-crime neighborhoods frictionless and efficient. The result has been the slow buildup of smart technology in what are for the most part disinvested communities. From the view of information capitalists, these communities represent a new accumulation frontier. In fact, they have sold so much data processing technology to urban police departments that a new branch of the carceral state has emerged: the real-time crime center. These datacenters are the panoptic towers that preside over an elaborate network of smart surveillance devices. What is more, the datacenters have been indispensable in exporting carceral power to the living spaces of the urban castaways.
The Origins of Crime Datacenters
Crime datacenters have their origins in War on Terror securitization. The turn of the twentieth century quickly brought federal, state, and city officials together to look for ways to modernize urban security infrastructure. One of the primary objectives, according to a Congressional Service Report, was to protect nodes of economic activity from terrorist attacks. In achieving this, IT and telecom companies turned to their well-established organizational logic, the network. Internet companies already had a model for developing infrastructure working closely with the government. Major companies received a considerable boost from Vice President Al Gore’s High Performance Computing Act (1991). The bill tapped private companies, including Ameritech, Delaware River, Pacific Bell, and Sprint, to bring together erstwhile disconnected internet networks on a national “information superhighway.” This was done in part by building facilities called network access points, which functioned as relays for the disparate networks. On the urban scale, telecommunication operation facilities, such as 60 Hudson and 32 Avenue of the Americas, routed internet networks from hundreds of carriers.
The War on Terror’s surveillance infrastructure was built according to these topological principles. Such infrastructure consisted of sprawling webs of devices that fed into central facilities. In achieving a state-of-the-art national security apparatus, the DHS and companies established network access points called fusion centers. The DHS also created the National Fusion Center Association, an eighty-member consortium of datacenters that connected data flows from the Coast Guard, departments of corrections, Customs and Border Protection, DHS, the Drug Enforcement Administration, the Highway Patrol, the National Guard, police departments, and private entities. The anatomy of these datacenters was at once decentralized and centralized. On one hand, they were made up of formerly dispersed networks of audio detection devices, environmental sensors, CCTVs, ground sensors, human patrols, and surveillance drones. On the other hand, the sprawling infrastructures condensed in centralized control rooms garnished with video walls that visualized data flows in maps, live video feeds, and statistical charts, graphs, and tables (Figure 20). The ultimate goal was to achieve full-spectrum dominance, or the ability to preempt unauthorized behavior through digital supremacy.
It was not long before public officials and corporations attempted to adopt similar surveillance systems to serve alternative purposes. In 2005, the George W. Bush administration revealed designs for a data fusion center for the Immigration and Naturalization Service’s Integrated Surveillance Intelligence System. DHS officials contracted the Boeing Corporation for the project, the Secure Border Initiative. The Bureau of Justice Assistance, Department of Justice, and Office of Justice Programs also began funding cities to establish datacenters for criminal justice. The result was a nationwide proliferation of real-time crime centers, or datacenters that processed data from a wide spectrum of sources, including audio sensors, dispatch systems, environmental sensors, license plate readers, precinct databases, service calls, and surveillance cameras. From an infrastructural standpoint, the goal of crime centers was to centralize the rapidly expanding surveillance infrastructures built during the War on Terror. From the standpoint of social management, crime datacenters were meant to function somewhat like information age equivalents to panopticon towers. But instead of prisons, entire neighborhoods were their analytical space. Motorola Solutions avowed that the analytical power of its real-time technology would make the need to respond to incidents a thing of the past, because, the company asserted matter-of-factly, the technology would prevent crime from happening in the first place. Active Solutions marketed cameras on grounds that they drastically reduced everything from violent crime to littering. RAND Corporation researchers argued that predictive analytics could be harnessed in these datacenters to control “deviant places” as different as U.S.-occupied parts of Iraq and high-crime parts of Minneapolis.
The ability to generate, circulate, and analyze vast aggregates of surveillance data from police departments, private businesses, and transportation authorities owed much to the emergence of long-term evolution (LTE) wireless networks. Pioneered by Nokia Networks, Ericsson, and NTT Docomo, these networks allowed for the unprecedentedly high-speed transfer of large quantities of data. In terms of surveillance infrastructure, one of the key benefits of LTEs was the ability to continuously stream high-resolution audio and video data. The resultant deluge of data created new opportunities for companies like ABM American, CineMassive, and Esri, and other vendors of data visualization tools. In some ways, William Gibson anticipated this meshing of corporate power, virtualization, and surveillance in his Sprawl trilogy. Gibson wove stories of a future in which someone who was linked into cyberspace could program a map to display all data exchanges. He emphasized that these exchanges were particularly intense in cities. As such, cyberspace attracted its share of industrial saboteurs, spies, and thieves, which compelled corporations to upload security programs called Intrusion Countermeasures Electronics (aptly abbreviated as ICE). Crime datacenters similarly create datafied models of urban space. Unlike Gibson’s Intrusion Countermeasures Electronics, city administrators and police patrols plugged into digital representations of urban space to probe for unauthorized behaviors in the real world. By abstracting urban terrain into data for the sole purpose of scanning, identifying, and capturing humans, crime datacenters simulate criminalized neighborhoods as if they were objects of continuous carceral management. This intrinsically millennial perspective was made possible by the availability of a widely diverse constellation of digital media. The datacenters structured the data and came to constitute a new node of carceral power.
Police in New York, Chicago, and Baltimore first explored designs for crime datacenters in the mid-aughts. In 2008, the Memphis Police Department introduced a $3.5 million surveillance network. Provided by SkyCop Inc., it was designed to be conspicuous with its “imposing towers, lights and cameras [that] signal police presence in a commanding way.” It was selectively deployed in neighborhoods such as Shelby Forest–Frayser (84 percent black), Parkway Village–Oakhaven (76 percent black), and White Haven–Coro Lake (94 percent black). The following year saw the city of Los Angeles launch its Real-Time Analysis and Critical Response (RACR) Division, which synthesized the surveillance operations of the Los Angeles Police Department’s Department Operations Center Unit, Department Operations Support Unit, Crime Analysis Section, Detective Support Section, and Incident Command Post Unit. Spectrum Integrated Technology Consulting Group helped design the LAPD’s control room, which is covered by video walls that display continuously updating incident maps, live video feeds, news feeds, seismic activity, service calls, and satellite imagery. The RACR provided a technical basis for the Los Angeles Smart Policing Initiative and the city’s Strategic Extraction and Restoration program to “extract” chronic offenders in the predominately latinx and black Newton Division, Southeast Division, Southwest Division, and 77th Street Division. As the decade turned, the Boston Police Department introduced a half-million-dollar datacenter that monitors the city’s emergency dispatch system, CCTVs, gunshot detective system, and radio communications. Its control room is embedded in the Boston Regional Information Center, which was designed to enhance coordination between federal agencies, police, and the private sector through a “net of surveillance over everyone in the Boston metropolitan region.” About 270 miles south of Boston, in Philadelphia, police introduced what eventually became the Delaware Valley Intelligence Center. Its control room accesses more than two thousand surveillance cameras and license plate readers, the majority of which are also used by the transportation authority. Around the same time, the Houston Police Department collaborated with Information Builders, a New York City–based software company, to design a $3 million digital surveillance infrastructure. The goal, according to the police chief, was to establish a “CompStat on steroids” by generating and crunching larger quantities of data than the celebrated NYPD. Similar projects cropped up across cities of variable sizes and regions: the Charlotte–Mecklenburg Police Department (CMPD) boasts 1,000 cameras operated by the area transit system, department of transportation, and police plus 140 license plate readers that perform 1.5 million scans per week; Detroit’s crime datacenter, the Public Safety Headquarters, includes a hidden network of cameras designed specifically to monitor homeless people.
By 2015, companies including AT&T, Cisco Systems, General Electric, IBM, Infineon Technologies, Intel Corporation, Verizon Enterprise Solutions, and Symantec AG found themselves in an IoT security industry reportedly worth almost $10 billion. The market overflowed with a diverse range of digital tools and services: Constant Technologies Inc. provides police with audiovisual connectivity and source routing and control; Motorola’s Real-Time Crime Solution Starter Kit integrates alarm, computer-aided dispatch, record keeping, sensors, and video systems; SkyCop’s Security Enclosure System offers intelligent video systems with analytic video monitoring, environmental monitoring, high compression digital recording, license plate recognition, and thermal image monitoring. The promiscuous entanglement of the IT sector and the security state had grown such that in 2015, the DHS opened its Silicon Valley office to fund market-based projects to securitize smart infrastructures across the country. For the private sector, the office was set up to communicate the needs of homeland security to start-up tech companies, fund research and development, and help firms accelerate the transition of security technologies to the marketplace. Such funding initiatives were enacted through the DHS’s Science and Technology Directorate’s Silicon Valley Innovation Program, which awarded more than $3 million to small tech companies around the country to build technology for border control, critical infrastructure, and cybersecurity. The same year the DHS opened its Silicon Valley office, police in Fresno, California, introduced a privately funded surveillance infrastructure made up of 140 traffic cameras, 180 police surveillance cameras, 400 officer body cameras, 750 public school cameras, and license plate readers that record 25,000 plates a month. The following year, the CMPD introduced its surveillance infrastructure. A large part of the CMPD’s acoustic detection infrastructure was paid for by federal grants originally awarded for the Democratic National Convention four years prior. The department used the surplus funds to upgrade its surveillance infrastructure in low-income areas with high crime indexes. It was yet another instance where the expansive thrust of the IoT security economy infiltrated marginal communities and hinted toward a digitally native mode of carceral management.
The Emergence of Domain Awareness in New York City
The potential of carceral power to be projected through digital infrastructure can be gleaned from New York City. From a global standpoint, IoT-based surveillance arrived somewhat belatedly in New York City. In fact, the great surveillance networks in London and Shanghai were objects of envy for New York City officials. The city’s lag was partially due to the fact that by the time the NYPD launched its first datacenter, the city was trending toward its lowest rates of serious crime in half a century. As such, data fusion first arrived amid counterterrorist initiatives in the downtown and financial districts.
Shortly after the War on Terror was declared, the NYPD unveiled its Office of Information Technology to upgrade its entire digital infrastructure. Part of the project involved establishing an NYPD-managed datacenter that had access to the city’s security systems. Its first order of business was converting NYPD record-keeping functions into database management systems. At the time, the department was using more carbon paper than any other agency in the city. To digitize the datasets scattered across the department’s seventy-six precincts, the police hired Dimension Data, a South African–based technology corporation. Together they developed hardware, digital forms and worksheets, and an entirely new and proprietary fiber-optic cable network. This laid the groundwork for a state-of-the-art surveillance infrastructure. About four years after the cabling was completed, the NYPD’s Counterterrorism Bureau approached Microsoft to assist the bureau with developing a smart surveillance network in the southern part of Manhattan. This was part of what was called the Lower Manhattan Security Initiative. The initiative gave rise to the Lower Manhattan Security Coordination Center, which oversaw three thousand cameras owned by the city and Wall Street firms. It processed data from more than 1.7 miles of biological, chemical, and nuclear detectors spread out across the southern part of Manhattan. Some of the cameras were capable of autonomous movement recognition; tagging physical objects, such as clothes or bags; and notifying the NYPD, Mass Transit Authority, Port Authority, and private institutions. The Coordination Center brought together a galaxy of data on arrests, crime suspects, ex-convicts, precinct crime rates, reported incidents, and warrants from city, state, and federal databases using IBM’s software. It ran pilot tests in the subway on video analytics software designed to identify hair color, facial hair, and skin tone. Five years following the launch of the center, a similar surveillance project commenced in midtown Manhattan. This extension of the city’s surveillance infrastructure materialized through a network of five hundred CCTVs in Grand Central Station, Penn Station, and Times Square. It was dubbed the Midtown Manhattan Security Initiative. The mayor explained that this datacenter was designed with intentions of establishing a supervisory infrastructure over “major centers of finance, commerce and government, transportation hubs and iconic landmarks.” In this phase of securitization, the city increased its total number of public- and private-sector cameras linked into fusion centers by nearly 160 percent.
While New York City’s surveillance complex was originally designed for counterterrorist operations, it was adapted to supervise the city’s surplus populations following the recession of 2007–9. The Great Recession and its detonation of impoverishment compelled city officials to securitize public housing complexes. Unemployment in the city increased an astounding 3 percent between 2008 and 2009. The Department of Labor reported that during this period, private-sector employment decreased by more than 2 percent, with great losses in the lower levels of the service industry. It was the steepest decline in employment in history of the city’s monthly unemployment data, totaling the highest number of unemployed persons (four hundred thousand) ever recorded. The racial structure of the recession was crystal clear. While unemployment hovered around 10 percent at the city level, it was higher in negatively racialized communities. The Russell Sage Foundation and Stanford Center on Poverty and Equality calculated that black unemployment was nearly twice that of white unemployment in Queens and more than twice that in Brooklyn and Manhattan. In 2010, black unemployment reached 16 percent, Hispanic unemployment about 12 percent, white unemployment nearly 8 percent, and Asian unemployment 7 percent. Whereas the highest-income neighborhoods had an average unemployment rate of 7 percent, the lowest-income neighborhoods averaged more than double that. These figures reached a median of 17 percent in the deteriorating public housing structures in black and latinx East New York, Central Bronx, and South Bronx. These dislocations, along with their attendant social problems, were met by the city in part by extending its digital disciplinary apparatus. If the city was to dedicate substantial revenues to these communities, it would be for disciplinary purposes.
Between 2006 and 2010, the city spent roughly $100 million to expand its fiber-optic network into the New York City Housing Authority (NYCHA). The goal was to bring some eighty-five public housing units into the orbit of the NYPD’s surveillance complex. With the cabling in place, the city’s technocrats proclaimed, public housing complexes could be placed under permanent supervision. The cables provided the necessary technical conditions for installing automated dispatch systems, criminal identification systems, high-resolution cameras, and shot-detection sensors in targeted sections of the Bronx and Brooklyn.
The Domain Awareness System (DAS) was the name of the datacenter that was made to manage the extensive web of digital surveillance. DAS was rolled out by city officials, IBM, and police personnel under the pretense of replacing the NYPD’s declining communications systems. The deputy commissioner of information technology estimated the project would require upward of $350 million. One of the first orders of business was grafting a webwork of cables that connected every NYPD facility underneath the city. Although the department traditionally relied on leasing its network services to telecommunications companies, its new cabling complex, FINEST 2.0, established a networked architecture exclusively for the police apparatus. FINEST 2.0 boasted hundreds of miles of cabling, increased precinct bandwidth by a factor of 100, and constituted a material foundation to expand the number of smart cameras throughout criminalized territories. For instance, in 2012, Domain Awareness added three thousand surveillance cameras. The number tripled within five years. Around this time, NYCHA estimated that the NYPD alone had installed 1,140 automated surveillance cameras in about 220 public housing facilities across the city. The perimeters of these facilities were also fortified by Mobile Utility Surveillance Towers and twenty-five-foot-tall SkyWatch towers. By 2016, NYPD officials had revealed plans to extend its fiber network into every NYCHA development in the city. One of the obstacles in achieving this, however, has been a lack of energy, cooling equipment, and physical space in the department’s existing datacenters. To rectify this, the NYPD secured a twenty-year lease on three floors in a skyscraper located at 375 Pearl Street, more commonly known as the Verizon Building.
This tremendous expansion of Domain Awareness in many ways echoes general theories of surveillance society. The system has automated databases as technical centerpieces and consists of a variegated infrastructure that continuously generates, retrieves, stores, analyzes, and transmits information about the public body. It is also by all accounts in a state of continuous diffusion and mutation. But its permeation in no way signals that the city will “effectively dispense with traditional methods like brutal public punishment [and] external controls and constraints.” There are, to be sure, at least two parallel surveillances: one that calcifies around centers of political economic power and consumerism, which erodes the civil rights of fully constituted citizens, and one that calcifies around devalued areas to erode the human rights of second-class citizens and noncitizens. Domain Awareness cross-fertilizes the territorial logics of the War on Terror, disciplinary logics of the War on Crime and War on Drugs, and infrastructural logics of IoT into a tactical grid of supervision. The system was in many ways organized to generate what Simone Browne describes as racializing surveillance, as it establishes an antagonistic relation between racial minorities and their surrounding environments.
The absurdly large datasets created through Domain Awareness infrastructure also created new opportunities for accumulating information capital. Tech companies eagerly lined up to address the department’s new need for data management and storage. The NYPD’s assistant commissioner of data analytics, deputy commissioner for information technology, and Strategic Technology Division officers estimated that a combined $600 million worth of funding from the DHS and federal forfeitures went into DAS’s information management architecture. This money was funneled into the IT sector through contracts for services for network administration, software and hardware maintenance, systems integration services, and video data wall services. Data processing emerged over the decade as one of the NYPD’s most dedicated tasks. The patrol officer does not simply administer sanctions but also plays bookkeeper for population management. By 2017, city officials reported that DAS held information on more than 100 million summonses, 54 million 911 calls, 15 million complaints, 12 million detective reports, 11 million arrests, 2 million warrants, and a month’s worth of video footage from nine thousand CCTV cameras. Within five years of operation, DAS was collecting, mining, and disseminating data from more than 5 million New York State criminal records, parole, and probation files; 20 million criminal complaints, emergency calls, and summonses; 31 million national crime records; and 33 billion public records. By 2013, the New York Times reported that the NYPD’s database housed 16 million data points on license plates. Only a couple years later, the number of data points had increased to 2 billion.
Data Fusion, Data Explosion in Chicago
Much like it did for New York City, the DHS catapulted Chicago’s crime datacenter and surveillance infrastructure. By the end of the 2000s, the secretary of homeland security had declared that no other U.S. city had a more extensive or integrated network of cameras than Chicago. Fusion centers first arrived in Chicago’s host state of Illinois in 2003. It was the same year that the Illinois State Police (ISP) opened its Statewide Terrorism and Intelligence Center in the state’s capital of Springfield. The center was linked into databases from the DHS, Federal Bureau of Investigation, Transportation Security Administration, Secret Service, and Treasury Department. It was also linked into the Chicago Police Department’s (CPD) Citizen and Law Enforcement Analysis and Reporting database, the Illinois Department of Corrections’ Offender Tracking System, and various other administrative databases. To manage the profusion of interdepartmental data flows, the state enrolled private data mining corporations, including Dun and Bradstreet, Experian, LexisNexis, and ISO ClaimSearch. Like DAS, the ISP’s intelligence center was characterized by the state using public revenue to pay IT companies to manage their surveillance data. And like DAS, the IT sector was eager to assist. The Black Belt provided the ideal site in which to do so.
Chicago’s digital surveillance apparatus expanded substantially as the new millennium moved forward. Midway through 2003, the CPD began to deploy surveillance pods “in areas where they’re needed and [that] enable us to increase the number of arrests in those areas.” Three years later, the city launched the Deployment Operations Center (DOC) (see chapter 3). The DOC began relatively small, comprising a commander and a dozen analysts who specialized in gangs and narcotics to generate target zones. The DOC also monitored feeds from field microphones, handheld devices, local area networks, patrol cars, and surveillance pod cameras. In 2007, the CPD opened another datacenter in the Crime Prevention Information Center (CPIC), which mined data from databases throughout state agencies, publicly and privately operated cameras, and the city’s gunshot detection sensors. The center also accesses some 1,260 cameras in “trouble spots” and 4,500 in public schools. CPIC cost $1 million to build, which was provided through the CPD’s operation budget, DHS grants, and seized drug money.
The city’s first major program to get a hold on the proliferating surveillance infrastructure was Operation Virtual Shield, which involved collaboration with IBM and its partners Firetide and Genetec. In addition to establishing a central command point over Chicago’s surveillance complex, the initiative involved dispersing more surveillance pods throughout the city. The pods were first introduced in the DHS under the pretext of securitizing potential terrorist targets. But another wave of pods occurred in majority black South Side and West Side communities shortly after. The city claimed that each camera in Virtual Shield was equipped with pan-tilt-zoom capability that allowed police to remotely rotate each camera and magnify its images. At five hundred feet, beamed the city and companies, such cameras could capture an object less than one inch thick. Virtual Shield cameras were also claimed to have the ability to act autonomously, courtesy of facial recognition software made by the NEC Corporation. Moreover, the smart cameras could be linked into the city’s mugshot database, which stored 4.5 million criminal booking photos. Such a unison of video analytics and interoperable databases gave rise to a radically new condition: machines could now track the movements of former offenders as they maneuvered through public space. Virtual Shield’s most cutting-edge component, the chief emergency officer declared, was its network of cameras that could “follow” machine-identified individuals and vehicles from camera to camera as they moved about the city.
Virtual Shield was largely responsible for bringing Chicago’s public transportation system into the CPD’s digital landscape. With more than $22 million from the DHS grants in hand, the city installed so many surveillance devices throughout the transportation system that it doubled its total number of cameras. In 2011, the city was operating an estimated ten thousand cameras. In a couple of years, the grants saw the appearance of some twenty-two thousand high-definition cameras across Chicago Transit Authority (CTA) buses, trains, and public transit stations. Anywhere from one to ten surveillance cameras were mounted in each of the eighteen hundred buses in the CTA’s fleet, some of which could be rotated 360 degrees by remote operators. The CTA also embarked upon a $14 million program to retrofit 850 older-model railcars with high-definition cameras. Many of the CPD’s squadron vehicles were also equipped with automated advanced license plate recognition, which matched plates with those stored in city, regional, state-level, and national databases in real time and notified patrol units of vehicles of interest.
Surveillance pods slowly began to saturate City Housing Authority facilities. The most conspicuous of these were attached on posts in public housing and lit up with flashing blue lights. Installing cameras was a typical solution by the city when responding to social problems either engendered or exacerbated by the Great Recession. Between 2008 and 2009, the Department of Labor and Bureau of Labor Statistics calculated that the monthly average unemployment rate for all residents of Chicago’s metropolitan region increased from 6 percent to 9 percent. It was nearly 16 percent and 12 percent for black and Hispanic residents, respectively (compared to 3 percent for residents classified as white). From 2007 to 2010, the percentage of people out of work for twenty-seven weeks or more rose from almost 23 percent to nearly 49 percent in Illinois. By 2012, almost a full third of residents classified as black lived below the poverty line, compared to 24 percent of those classified as Hispanic and nearly 15 percent of those classified as white. The same year witnessed a 27 percent decrease in Illinois teen employment, which reached the lowest in the state’s recorded history. Approximately 92 percent of males aged sixteen to nineteen categorized as black and 80 percent of those categorized as Hispanic in the city of Chicago were jobless during the year. Illicit markets propagated, and the rate of drug killings increased by 38 percent.
Police violence was the crudest of the city’s responses to deteriorating conditions in the Black Belt. A report by the city found that from 2007 to 2015, more than fifteen hundred CPD officers acquired ten or more complaint registers, sixty-five of whom received thirty or more. Approximately 40 percent of the complaints were not investigated by the Bureau of Internal Affairs or the Independent Police Review Authority. The violences inherent in Chicago’s approach to handling negatively racialized poverty were punctuated by the video of Officer Jason Van Dyke shooting seventeen-year-old Laquan McDonald sixteen times in 2014 for walking away from him during questioning. This triggered a storm of protest, which achieved its most potent expression the following November, when hundreds of people marched into Chicago’s downtown retail district, the Magnificent Mile, at the apex of the shopping season. The spectacle of Chicago’s quarantined black and latinx subjects seizing urban centers of conspicuous consumption revealed the city’s racially binarized structure. Human antivalue came face-to-face with centers of valorization, the explosive implications of which prompted Mayor Rahm Emanuel to assemble a task force on policing and racism. The task force report concluded that several normalized CPD practices gave “validity to the widely held belief the police have no regard for the sanctity of life when it comes to people of color.” The report paid special attention to the fact that about 75 percent of CPD shootings, 72 percent of street stops, and 76 percent of taserings involve black or latinx subjects, though these groups make up 60 percent of the city’s population. The same spectacle opened space for the ACLU, Black Lives Matter Chicago, and the NAACP to pressure the city to devise a consent decree. Black Lives Matter also mobilized protests at City Hall in response to plans to open a new $95 million police academy in 2018. The city’s agreement to the decree, which established new rules for use of force, hiring and retention, and transparency, was in many ways an armistice meant to defuse demands to defund the CPD and criminally prosecute Mayor Emanuel for concealing police murders.
While organized resistance to police terror was mounting, the city established six Strategic Decision Support Centers, or “hyperlocal intelligence centers,” to orchestrate patrol deployments in Englewood and Harrison. Less than a year after launch, the CPD’s Bureau of Technical Services announced plans to create an additional four centers at a consumer electronics show in Las Vegas. A year later, the city announced plans to open eleven more centers. The centers were staffed with CPD intelligence officers and University of Chicago Crime Lab analysts. The expansion was to take place alongside the hiring of one thousand additional officers and a tenfold increase in the CPD’s automated gunshot detection system that spans 110 square miles.
Crime datacenters are powerful tools for invisibilizing and normalizing the methods by which cities administer racial criminalization. It is no coincidence that the influx of formerly incarcerated persons into peripheral urban communities has proceeded alongside the rise of digital architectures of police supervision. At present, there are 5 million formerly convicted people in the United States, 27 percent of whom are unemployed, a figure comparable to the Great Depression. These individuals are structurally locked out of contemporary urban economies, which revolve around consumption, finance, real estate, and technical knowledge production. Such are the conditions in which carceral power merges with smart urbanization.
In some city, someone on probation is wearing a GPS monitor while he walks to an automated kiosk to check in with his probationer officer. In that same city, a child passes through a metal detector to enter a school that was targeted by geographic information software for heightened policing. An employer is running a background check on an ex offender, while a gentrifier scrolls through neighborhood crime rates to decide where to live. A police officer uploads a suspect’s fingerprints into a mobile device, while a security camera notifies another officer about a person of interest. The vast nexus of smart machines that branches out from these centers forms the backbone of hypercarceralization, a digitally native carceral power that is hyperrealist in its preoccupation with computer simulation; hypertextual with its boundless web of documents; hypermediated with its profusion of audio, graphics, and video; and hyperactive in its inexorable surveillance and assessment. At the core of this monstrosity is the power fantasy of city administrators, corporations, and large parts of the public to establish a human filtration system. While this is only an aspiration, and a latent one at that, it is an aspiration immanent to smart urbanization. In fact, the determination to quarantine criminalized populations from these cities is so intense that it has birthed its own unique carceral apparatus, the crime datacenter—the warden of criminalized communities.
All of this is made possible by the convergence of the carceral state and IoT. The result is an actual material network of cabling, cellular towers, energy sources, sensors, and smart devices. Such an achievement is not being assembled out of concern for the well-being of those who inhabit places overlain by the network. For the IT sector, the mad rush to invest in criminal justice infrastructure is an innovative way of finding value in devalued urban populations and places. For cities, the infrastructure provides a new medium to execute an old form of racial management. Domain Awareness is programmed to look for the same demographic groups and neighborhoods that were besieged by mass incarceration. This is certainly true of the surveillance technology grafted into public housing facilities, which lies like carceral carapaces around the lifeworlds of devalued populations.