The network logic epitomized by the Internet became applicable to every domain of activity, to every context, and to every location that could be electronically connected.
—Manuel Castells, The Rise of the Network Society
The protocols of the punitive state pulsate through communications cables and across wireless networks—sometimes at the behest of an algorithm. This is because state-authorized punishment can now be administered through the internet and web applications. On one hand, the internet serves as a medium for criminal justice agencies to agglomerate information about the public through an immense number of sources. The ability to bring diverse datastreams into central databases has given rise to a massive registry of “aliens,” felons, misdemeanants, political radicals, potential offenders, sex offenders, and (potential) terrorists. In some cities, the public can submit information about suspected offenders to enforcement agencies via the web, making punitive governance an increasingly crowdsourced affair.
On the other hand, criminal justice information constantly flows from state agencies into mobile devices throughout the public sphere. Before the internet, one would have had to travel to repositories in government buildings, then comb through vast paper archives to confirm that a person held a criminal record. Now, the police and corrections apparatuses publish records on arrestees, early release offenders, inmates, low-level offenders, parolee sex registrants, sex offenders, and wanted fugitives on the web. Sometimes these profiles are supplemented with photographs and personal information. Private traders of the records employ bots to farm new ones from criminal justice websites. These traders eventually formed the background-checking industry, which has grown such that it established a trade association, the National Association of Professional Background Screeners, in 2003. The association consists of just under one thousand firms that sell information about convicted persons to banks, employers, insurance companies, landlords, and state agencies. Some background-checking websites charge people to remove their information from the sites. Nonprofit organizations also publish specialized registries that focus on different types of offenders. Many newspaper websites have taken to publishing photo galleries of mug shots on the web as well. Liberal websites publish galleries of people who have been accused, though not convicted, of sexual misconduct as clickbait. Never before has it been so difficult to keep a criminal record from becoming public knowledge. As a result, more institutions can work in concert with penal authorities, including educational institutions, employers, public housing administrators, and social welfare agencies.
The newfound ability to instantly identify former offenders reflects the extent to which the penal state has adapted to the information superhighway’s organizational template, the network. In its essential form, a network is a centerless system of cells whose core command functions are distributed across various nodes. Networks multiply their power by increasing the number of these nodes. “When they diffuse,” notes Castells, “their growth becomes exponential, as the benefits from being in the network grow exponentially.” To be sure, networks of racialized surveillance have existed in the United States since at least the Fugitive Slave Act of 1850, which spawned a network of specially appointed magistrates, civilians, and newspapers to differentially monitor blacks (this in turn catalyzed an oppositional network in the Underground Railroad). Another example was the system of networks established between indigenous scouts and the U.S. Army during the Indian Wars. But none of these could match the ubiquity and inexorability of today’s internet-based criminal identification networks. Today, millions of interconnected databases, cameras, human users, and smart devices stream information about criminalized populations to the entire public body in real time. Processing and sanctioning offenders is no longer confined to state facilities. In fact, now the penal state can theoretically authorize punishment anyplace there is a wireless connection.
The penal state’s quiet mutation through wireless networks is creating conditions hospitable to new topologies of state-authorized punishment. For patrol forces, these networks allow officers to register sanctions into databases while they are still in the streets, thus extending criminal processing to public space. Networked criminal justice databases also have deep implications for criminal identification. By 2007, the NCIC confirmed that it processed a wanted person hit every ninety seconds. What is more, web technology allows the police to mobilize the public as sentinels for surveillance and the courts to highlight those whom they convict to employers, landlords, schools, and the public at large. The mergence of the web and mass criminalization has invoked the unsettling image of a wireless apparatus that can monitor and sanction former offenders as they move from point to point across various institutional landscapes. The image, to be sure, emerged well before the internet explosion in the 1990s.
Building a National Criminal Identification Network
Throughout the turbulent 1960s, the Federal Bureau of Investigation (FBI) sought congressional approval to build a nationwide criminal identification network. It got its chance toward the middle of the decade, when the Identification Division proposed leasing data processing hardware to aggregate criminal history records, incident reports, and wanted notices from law enforcement agencies in the Washington, D.C., metropolitan region. The proposal emboldened the FBI to build a computer network that connected information systems from law enforcement agencies in the country. The result was the National Crime Information Center (NCIC), a hub that brought together criminal justice databases on a national scale. The network, which comprised fifteen city- and state-level computer systems and processed fifty-five hundred transactions daily, was activated in 1967.
A key moment in NCIC history occurred when a New York Police Department (NYPD) officer radioed the center to look up a license plate. Within a minute and a half, the story goes, the officer was given the plate number and notified that the car was stolen. The incident was taken by many in the bureau as an example of the power of networks. It found that telecommunications networks established a medium through which patrol units, dispatchers, and centralized databanks could collectively form a dynamic chain of surveillance, identification, and interception. The revelation was characteristic of the zeitgeist. During the NCIC’s early phases, the Information Processing Techniques Office’s Advanced Research Projects Agency (ARPA) mulled over designs for interactive computing networks. The result was ARPANET, a computer network designed by the engineering firm Bolt, Beranek, and Newman courtesy of a $1 million contract with the Defense Department. ARPANET employed a revolutionary telecommunications technology developed at RAND Corporation and the British National Physical Laboratory, packet switching, which defined rules for data transmission over the internet. ARPANET made its first successful data transmission at the inaugural International Conference on Computer Communication in 1972. This established the foundation for the internet.
While computer science and technology were flourishing at West Coast universities, the national War on Drugs was beginning to take form. Political scientist Marie Gottschalk chronicled how the politics of punishment had grown to such an extent in the United States during the 1970s that it commanded bipartisan support. In addition to familiar conservative factions, activists from the American Civil Liberties Union, National Organization of Victims Assistance, and Mothers against Drunk Driving drove the expansion of penal populism in the 1970s. As the penal state began to crystallize around this especially toxic populism, the NCIC embarked on a national project to link all criminal justice information systems in the country. The center marshaled LEAA funds for the System for Electronic Analysis and Retrieval of Criminal Histories (SEARCH) project to “demonstrate that a computerized criminal offender file, containing data from all segments of criminal justice, can be standardized and exchanged between States on a timely basis.” The project was spearheaded by the SEARCH team, a multimember firm that acted as a liaison between criminal justice information scientists and the IT sector. The group oversaw construction of the Computerized Criminal History database, which stored the aliases, arrest dates, charges, dispositions, fingerprints, names, and physical descriptions of serious offenders. In little over a year, the SEARCH project unveiled an incident report database using an IBM 360/65 central processor in the Michigan State Police headquarters. It was linked into police databases in five other states. Members of the SEARCH team downplayed the praise its database received for drastically reducing the amount of time it took to retrieve criminal records. Instead, the group, which went on to found the National Consortium for Justice Information and Statistics and SEARCH Group Inc., emphasized that it would revolutionize the state’s ability to coordinate action across departments.
Constructing a database network on a national scale required standardizing criminal justice datasets. Luckily for the technocrats, the 1970s was a watershed moment for communication protocol standardization. In 1973, designs for Transmission Control Protocol (TCP) were established at Stanford University, which laid the groundwork for Transmission Control Protocol/Internet Protocol (TCP/IP). The protocols were, in essence, rules for digitally breaking down messages from one computer, transmitting the pieces, and reassembling them on another computer in another location. While these rules were being formalized, the NCIC was initiating the Comprehensive Data System program to standardize the development of criminal justice information systems on state and municipal levels. The initiative required that new software for criminal justice agencies be designed according to federal standards in order to receive financial support. In addition to technical standards, the NCIC format categorized all data into two sets: one consisted of seven property offenses, the other of twelve offenses against persons. The LEAA dispensed $207 million in categorical grants and upward of $40 million in block grants to states to build comprehensive data systems and statistical programs compatible with the SEARCH prototype. Moreover, national regulations on crime data management were established in 1976. By 1980, SEARCH’s database model had spread to every state, and all state governments had access to the NCIC’s centralized system.
The telecommunications industry’s services were summoned to transmit the coming data torrent. At the time, the largest criminal justice communication network was the Law Enforcement Teletype System. Founded in the previous decade, the network was hampered by terminal information overload, extraordinarily slow message delivery, and an inability to automatically retrieve remote data. The LEAA thus awarded $4 million to the National Law Enforcement Teletype System Inc. to “provide the technology to carry the present and predicted [data] traffic load and to make possible computer-to-computer exchanges of communication.” This marked the birth of NLETS Inc., which manages a network of terminals and systems for municipal, regional, state, and national criminal justice agencies to this day.
The massive project undertaken by the NCIC eventually involved upgrading the Uniform Crime Reporting system (UCR) through the National Incident-Based Reporting System (NIBRS). The new system was built using funds from the Bureau of Justice Statistics and FBI that were authorized through the Crime Identification Technology Act (1998), a bill aimed to establish an information network between eighteen thousand law enforcement agencies. SEARCH Group Inc. functioned as a go-between for the $100 million of federal funding and the IT vendors that eventually built the database network. Firms such as Crimestar Corporation, Constellation Software Inc., and Omnigo Software quickly turned to developing NIBRS-compatible software. In contrast to the UCR, which updated monthly, NIBRS took data from law enforcement the instant they were entered into databases.
NIBRS was a beneficiary to the dramatic expansion of the web. Web browsers first appeared in 1990, courtesy of programmers and engineers at the European Organization for Nuclear Research who developed hypertext languages and transfer protocols to facilitate interactions between web browsers and database servers. The FBI used Hypertext Markup Language (HTML) to link up criminal justice databases and to create unique tags for criminal justice data. So long as agencies were using the same tags, they could freely share information with one another.
Similar developments took place in the police apparatus. Midway through the decade, the FBI Law Enforcement Bulletin began collecting information on how municipal agencies were using the internet. The project revealed that dispatchers, patrol officers, police chiefs, students, and professors used it for researching databases and discussing current trends in law enforcement with practitioners and researchers around the world. By 1992, the IACP had established a network between databases from 425 law enforcement agencies. A few years after, Chicago, Phoenix, and Sacramento had web pages to broadcast alerts, organize community policing groups, report crimes for cash, and review rewards for wanted suspects. At the same time, the FBI launched its Criminal Justice Information Services (CJIS) Division to act as a hub for the intelligence community, law enforcement, and national security. Software companies like LEA Data Technologies and Target Solutions and Power DMS were obliged. One of the CJIS’s early projects was an electronic gateway for enforcement agencies called Law Enforcement Online, which facilitated online education modules on subjects ranging from forensic anthropology to antiterrorism tactics. The gateway provided multimedia libraries of documents, publications, research, and technical bulletins and a Virtual Command Center where users could submit and retrieve maps, messages, photo images, and suspect files. It also had a virtual community-building application, which included more than one thousand specialized groups. The CJIS also oversaw the implementation of the National Data Exchange (N-DEx), a repository for data on arrests, booking, computer-aided dispatch calls, incident reports, calls for service, field contacts, identification records, parolees/probationers, pretrial investigations, supervised released reports, traffic citations, and more. Corrections personnel, detectives, patrol officers, parole and probation officers, and regional dispatchers all contributed to and took information from N-DEx for everything from routine investigations to SWAT raids.
This networking of enforcement agencies slowly built up a massive database network of criminalized and precriminalized subjects. Police across states started to share access to massive gang data clearinghouses through a closed network called GangNet, a commercial, proprietary system purchased by the Bureau of Alcohol, Tobacco, Firearms, and Explosives’ Information Services Division. The system, developed by Orion Scientific Systems Inc., was designed so that patrol units could supply and retrieve data about individuals in, or suspected of being in, gangs, as well as data about gang hangouts, the residences of gang members, and their vehicles. GangNet was also linked into the erstwhile Immigration and Naturalization Service, which increased the exposability of criminalized noncitizens. At this point, however, smaller jurisdictions were not linked into the national database network. To address this, in 1995, the Bureau of Justice Statistics, state-level criminal justice agencies, and the FBI launched the National Criminal History Improvement Program (NCHIP). Over the next decade, NCHIP directed hundreds of millions of dollars into establishing a national criminal justice reporting network with an unprecedented number of agencies. In its first year, it gave more than $112 million in direct awards to states and eligible territories to develop law enforcement databases compatible with NCIC’s system. The Crime Identification Technology Act (1998) expanded the program by transferring funds to software companies in the SEARCH Group’s exclusive market niche. NCHIP helped states automate case and record databases, convert juvenile records to adult case management systems, and establish sex offender databases. It also aided states in making automated databases for fingerprint and other biometric data. Between 1995 and 1999, the number of crime history records increased nearly 30 percent nationwide, and the number of automated records accessible to the NCIC’s users increased 35 percent. Part of this was due to the addition of criminal immigration violations to the NCIC’s central database in 1996. NCHIP also transferred millions of dollars to the National Instant Criminal Background Check System, which established instant interstate identifications to users in the system. From 1999 to 2003, the number of state records in the NCIC database went from 3,222 to 88,696.
As more and more data flowed through the rapidly proliferating network, the NCIC required considerable technical upgrades. This positive feedback loop constituted a boon for information capital. Indeed, the NCIC eventually came to provide a telecommunication network to the CJIS Systems Agency in each state. Smaller companies, such as Applied Technologies Inc. and Diversified Computer Systems, stepped in to fill this state-induced demand. As the new millennium drew closer, the bureau introduced NCIC 2000, which managed more than twenty-one databases and could search through others using various communications protocols and could be used on portable smart devices. This dramatically increased the data that flowed into the national center. For instance, NCIC 2000’s databases stored biometric and genetic data, including DNA, facial patterns, fingerprints, irises, palm prints, and voice patterns. These data are transferred into a closed network of databases, including the Criminal History Record Information system, the Combined DNA Index System, and the Repository for Individuals of Special Concern. Patrol units in the field can search for matches through the millions of entries and submit digital photographs and fingerprints.
To manage this galactic explosion of data, technocrats went so far as to develop a new transmission and communications protocol exclusively for criminal justice agencies. In 2002, the Bureau of Justice Assistance launched the Law Enforcement Information Technology Standards Council, which—along with the Integrated Justice Information Systems Institute and a “functional standards” committee of law enforcement personnel and technology corporations—established national protocol standards for record management systems and computer-aided dispatch systems. The scope of the project was so grand that it called forth the development of a new universal markup language for all criminal justice agencies. These labors materialized in the Global Justice XML Data Model (GJXDM), which established a foundation for data sharing across municipal, state, national, and international enforcement agencies. The centerpiece of the model is the Global Justice XML Data Dictionary, which is made up of two thousand unique data elements.
The War on Terror dramatically expanded the role of the federal government in the bourgeoning network of law enforcement databases (see chapter 5). In 2005, the Departments of Justice and Homeland Security mandated that tech companies that supplied law enforcement information systems had to use GJXDM to receive federal funding for research and development. This requirement gave birth to yet another data exchange model, the National Information Exchange Model, which established a standard lexicon for criminal justice agencies, homeland security apparatuses, and private corporations. (Homeland security’s heightened role in the development of law enforcement databases also prompted the IACP to organize a Criminal Intelligence Sharing Summit, which eventually gave rise to an information-sharing network of police and government agencies across the Global North.) The influence of network logics also penetrated the nation’s largest law enforcement agency, Immigration and Customs Enforcement. In 2006, the George W. Bush administration revealed designs to augment border policing with the Secure Border Initiative’s “virtual fence,” dubbed SBInet. Its ultimate goal was to endow border personnel with the ability to identify, track, digitally represent, and capture unauthorized subjects with unprecedented swiftness. SBInet was intended to unify and animate networks of unmanned aerial surveillance, control rooms, data terminals, ground sensors, radar and camera towers, and vehicular patrols using artificial intelligence (AI). Specifically, the AI was supposed to be designed to ascertain all security breaches into national territory, determine who or what is crossing, and notify the Border Patrol unit best positioned for interception. Boeing Corporation prototyped the ill-fated SBInet with $3.7 billion worth of federal funding.
The NYPD’s Mobile Networks
If we zoom down to the urban scale, we see a variegated ensemble of actors and processes behind the spread of penal networks. In fact, the combination of the network form, digital technology, and differential policing and punishment predates the internet at this level. Midway through the nineteenth century, police in Boston, New York, and Philadelphia used the telegraph to coordinate quick responses to urban uprisings fueled by everything from anti-abolitionism to government graft, nativism, and rising food prices. The core function of police telegraphs was to facilitate communication between central headquarters and precincts. Near the end of the 1860s, the Gamewell Fire Alarm Company extended telegraph networks through electrical signal boxes situated throughout beat patrol routes. As the century turned, police telegraph systems were integrated with telephony to multiply the number of signal booths throughout cities. These hybrid networks were used to dispatch patrol wagons to aid in the suppression of organized crime and popular uprisings. But with the unrivaled power of web technology that arrived toward the end of the century, the police apparatus could exploit the network form not only for emergencies but also for everyday patrolling and punishment.
In New York City, early attempts to implement the NYPD’s web technologies were mostly for internal bureaucratic purposes. During the 1980s, the NYPD made several strides in providing personnel with remote access to its central database. Administrative staff retrieved information from mobile digital terminals that ran online booking and warrant applications. These provided personnel throughout the department summaries on cases that included arrestee names, charges, fingerprints, officer ID numbers, photographs, and information on the race, sex, and date of birth of offenders. Similar sets of interlinked databases appeared in district attorneys’ offices and throughout the court system. But at the time, these systems, like those used by NYPD bureaucrats, were used for internal administrative functions.
The city’s network of criminal justice databases experienced a qualitative leap in the 1990s, when technocrats started to see the greater potential of digital networks. Indeed, the mid-1990s saw the Public Access to Court Electronic Records (PACER) go online, which was intended to allow the public to obtain information on cases and involved parties. Such technology was made possible by the declining costs and increasing processing power of commercial computing. These factors placed mobile database terminals at the center of the NYPD’s Community Patrol Officer Program initiative, a project to enroll the public to put their “eyes and ears on the street” to combat criminals. By 1990, the NYPD estimated that it actively mobilized 65,000 civilians into 150 community patrols: 15,000 civilians into the city-sponsored block watch program, 8,864 into tenant–building civilian patrollers, 7,000 into civilian motorized patrollers, and 1,216 into on-foot civilian patrollers. The department proposed publicly accessible databases as one way of organizing and harnessing the collective power of civilians. In addition to being efficient repositories, the police commissioner argued in the beginning of the 1990s, public databases could be used to augment the NYPD’s ability to monitor, detect, and intercept problematic people. Just a few years before IBM released the first smartphone, the police commissioner described a world in which access to constantly updated police data was a prerequisite for being an informed citizen. Each precinct in the city was thus outfitted with a database terminal for civilians to view crime statistics, information on rules and regulations, and official procedures for crime reporting. Such was the beginning of modulating part of the public into a living and breathing appendage of the police apparatus.
The community policing initiative also involved equipping patrol officers with handheld computers to provide them with access to the police database network. Mobile terminals were installed in squad vehicles during the Dinkins administration (1990–93) so that patrol officers could tap into the NCIC and the New York State Police Information Network’s databases. The city’s technocrats boasted that the terminals would revolutionize patrol units, as they offered instant access to arrest records, beat books, complaint reports, court orders, information on driver’s licenses, location histories, registrations, and wanted persons. By jacking into the network of databases, insisted NYPD technocrats, the department’s investigations, situational awareness, and warrant enforcement would be enhanced dramatically. Accessible databases were also seen as a means by which patrol officers could capture additional data about the public during each and every police–civilian interaction. The mid-1990s thus witnessed the city transfer criminal booking procedures onto the street through digital networks. This phenomenon was made possible by wirelessly connected databases that allowed patrol units to register quality-of-life offenders almost anywhere in the city. For instance, the Transit Bureau introduced a Mobile Arrest Processing Center—the “bust bus”—a van outfitted with computers, cellular phones, and fax machines to file paperwork and execute search warrants. The mobile center was meant to slash the amount of time required to process people apprehended for low-level citations during subway sweeps from twenty-four hours to a matter of hours. It was also supposed to reduce the amount of time that low-level violators spent in custody and eliminated the need to transport subjects to district commands for background and warrant checks.
Just as with the NCIC, the increased dispersion of users in the NYPD’s database network mandated increasingly centralized controls. As the century closed, the city also began to centralize its IT research and development. Until then, city agencies had incorporated technology at their own discretion, leading to inefficient data-sharing practices. These factors left the city’s bureaucracies far behind the private sector in terms of technical cohesion and thus advancement. In 1998, the Giuliani administration (1994–2001) issued Executive Order 43, which established the Technology Steering Committee and Office of Technology in the Department of Information Technology and Telecommunications. The committee was tasked with optimizing communications between government agencies. In the area of criminal justice, these initiatives led the city to find that the more interlinked its databases were, the more effective it was in identifying, monitoring, and capturing targeted persons. The Department of Information Technology and Telecommunications thus played a part in the rise in initiatives to use database networks to register and track graffiti artists, gun violence, narcotics offenders, peddlers, juvenile offenders, and sex workers. For instance, in 1995, the Criminal Justice Coordinator, Department of Juvenile Justice, and Law Department assembled a joint juvenile justice database, the Comprehensive Justice Information System. The Gambling Control Commission teamed with the Trade Waste Commission to assemble a database for organized crime. As the century turned, the Human Resources Administration’s welfare-to-work programs for drug use offenders began using the web to facilitate information exchanges with substance abuse treatment centers.
Integrating the vast ecology of administrative databases remained a chief concern under Michael Bloomberg’s administration (2002–2013), which, in 2002, appointed the first deputy commissioner of the Office of Information Technology (OIT) (now the Information Technology Bureau). As a former chief information officer from the IT sector, the OIT deputy commissioner’s first major project involved the wholesale upgrade of NYPD databases and communication systems. The OIT constructed a versatile suite of analysis and investigative support applications made up of the Crime Data Warehouse, the Enterprise Case Management System, a license plate database, and the Real-Time Crime Center (see chapter 5). It also established an online database that stores all data related to arrests, complaints, and summonses.
The steady proliferation of the city’s database network extended to the parole/probation apparatus. The Systems Department of the Criminal Justice Agency (CJA) was a central agency in this regard, as it was made up of programmers tasked with maintaining an automated database to manage data on all arrests, court appearances, and case dispositions in the city. The Systems Department was also summoned to manage the CJA’s local area network of personal computers and its wide area network of borough offices. Furthermore, the department managed the CJA’s Ethernet, fiber-optic cabling, firewalls, and servers. By 2003, the CJA unveiled its own database, which contained information on almost every adult arrested and issued a summons in New York City. It automatically aggregated data from the Department of Corrections, NYPD, and Office of Court Administration, in addition to community-based, criminal history, and demographic information collected by CJA researchers during prearraignment processing.
New York City officials’ newfound ability to instantaneously collect, calculate, and circulate enormous data quantities through networks has quietly modified the patrol function. In fact, the database network allows the carceral state to displace many of its administrative functions into urban space through police patrols. Within an instant, patrol officers dispersed throughout the public sphere can access federal databases, license plate reader databases, New York State’s Office of Court Administration databases, and state databases. Moreover, the ability to remotely enter information into databases increased the record-keeping tasks of police patrolling, which is increasingly defined by “producing numbers.” For instance, in 2014, the Information Technology Bureau equipped thirty-five thousand officers with smartphones and two thousand patrol vehicles with tablets in a $140 million mobility initiative. In the mobility initiative’s initial rollout, officers were given Nokia mobile phones. But Microsoft discontinued support for the operating systems used in the models soon after, which prompted the Strategic Technology Division to take advantage of the NYPD’s contract with AT&T to replace the Nokia phones with iPhones under the pretext of a hardware upgrade. Wasteful though the ordeal was, city officials confidently told the public that mobile platforms were the “single largest driver of information technology growth in the Department.” One goal of the mobility initiative was to provide patrols with access to the NYPD’s Crime Information Center and enable them to perform fingerprint scans; check information on Crime Stoppers, missing/wanted persons, and warrants; and translate non-English speech into English (see Figure 17).
The mobility initiative represented how network power allowed the city to relocate offender processing procedures from administrative buildings, jails, precinct station houses, and prisons onto the streets. This shift was evidenced by eruptions of recorded disorderly conduct violations, quality-of-life offenses, and victimless misdemeanors. By enabling the transference of offender processing to the police, wireless networks brought the bureaucratic side of the punitive state into city space. From the time that NYPD patrol units had mobile database terminals until 2003, annual misdemeanor arrests for drugs other than marijuana went from 19,082 to 37,460; arrests for marijuana went from 5,221 to 60,190; person-related charges went from 18,186 to 33,600; and vehicle-related driving violations went from 6,783 to 24,000. In the process, the police built up a massive database of low-level offenders. Moreover, from 2000 to 2010, the city made an average of 136,954 major felony and 68,620 non–seven major felony convictions per year.
The city’s capacity to register offenders and violators on such massive scales enabled it to exclude large segments of the population from the formal channels of social reproduction. In New York, felonies can lead to a termination of parental rights; in employment, felonies can restrict one from federal office and employment by the U.S. government; in federal aid, they can restrict one from federal assistance if one was receiving aid during the conviction; in housing, they can lead to evictions; in terms of marriage, life sentences render one ineligible to marry; in public benefits, they can disqualify one from receiving cash assistance, contracts, commercial licenses, grants, loans, and professional licenses funded by the United States. Some felonies also exclude some subjects from the public sphere: in jury service, they can restrict one from federal grand, state, and petit jury. In short, the punitive state’s network is a necropolitical network, as it is designed to maintain barriers between criminalized populations, formal avenues of social reproduction, and political rights.
Criminal Justice Database Networks in Illinois
In contrast to New York, Chicago’s database network was assembled for the most part at the level of the state. Since the Criminal Identification and Investigation Act (1931), the Illinois State Police (ISP) has managed the central repository for all criminal justice data in Illinois. Four decades after the act appeared, the ISP took part in NCIC’s Comprehensive Data System program to develop a crime database network that traversed all criminal justice agencies in Illinois. Called the Computerized Criminal History (CCH) system, the ISP’s model was originally built for internal purposes. The overarching goal was to establish a repository for corrections personnel, law enforcement, judges, and state attorneys to retrieve criminal records. Attorneys used the database for recommending bail; correctional officers used it for determining security levels; law enforcement used it for investigations; probation officers used it for determining supervision techniques and treatment; and judges used it for pretrial release and sentencing. Civilians were also able to purchase information from the CCH database, including the fingerprints, name, race, sex, and birthdate of convicted persons.
The CCH database was unveiled around the same time as the state’s first digitized booking, monitoring, and security database. Both were built in the first instance to help manage Illinois’s expanding carceral population. Between 1974 and 1983, the number of imprisoned persons in Illinois doubled, triggering an overcrowding crisis whose effects rippled across state agencies. And as carceral conditions grew more brutalistic, Illinois found itself ranking fourth in jail suicides. Many technocrats in the Illinois Criminal Justice Information Authority (ICJIA) believed that updating and adding several new features to the CCH database would allow for more efficient management of overcrowded facilities. The ICJIA was established in 1983. Its overriding objective was to optimize criminal justice administration through digital technologies. With the carceral crisis rising, the ICJIA embarked on a project to update the state’s correctional database systems and eventually linked them across the web. The first step was to clean data throughout criminal justice agencies. Auditors found that CCH records were not up to date, lacked adequate security, and were missing disposition and racial information. But technocrats assured that “technology in [criminal justice] seems to come in waves, and a very big wave is about to break.” Interoperable databases were at the head of this latest wave. With database networks, believed technocrats, state authorities would be able to receive all types of information about each individual prisoner, which would allow for more effective cell assignments, disciplinary techniques, medical attention, and more. And so the Criminal History Records Information Act was unanimously approved by the Illinois House in 1983. The act stipulated that all criminal justice agencies would have to submit charges, convictions, dispositions, and fingerprints to the CCH database network in a uniform manner. This, experts held, would aid correctional officials in classifying inmates, judges in categorizing offenders, law enforcement in investigations, probation officers with presentence investigations, and state attorneys in deciding upon charges. Over the course of the decade, all circuit court counties, correctional facilities, sheriffs, state’s attorneys, and police departments were eventually made to submit arrest, charge, custodial, disposition, and fingerprint data to the CCH network.
Before CCH was upgraded, human operators arranged this information into different categories—arrests, dispositions, custodial receipts, and status changes—and then sent them to the state’s criminal justice database. The information was sent through computer tapes, electronic submission, and paper submission. The database included information on inmate arrivals, appeals, releases, sentence commutations, and deaths, in addition to circuit court and state’s attorney depositions. During the early 1980s, police departments throughout the state began adopting network principles of the internet to optimize its data pipelines. Police began linking into the Police Information Management System (PIMS), one of the country’s first systems allowing police to share information through a common network. PIMS established a statewide network in which departments exchanged arrest, fingerprint, home address, incident, property, and vehicle information. It also hosted physical descriptions of convicts and suspects. Just one year after launch, the Information Authority turned to supercomputing to accommodate the rapidly increasing number of agencies in the PIMS network. Toward the end of the decade, patrol vehicles were outfitted with mobile data terminals so that officers could enter information directly into databases. One of this system’s most innovative features was that it enabled patrol officers to check license plates, which allowed police to check for warrants on motorists. Thus the patrol unit became a mobile node in the punitive state’s information network.
This increase in “police productivity” put considerable pressure on courts, resulting in a backlog of caseloads. The Information Authority determined that the rapid growth in the court backlog would triple the average time it took to process criminal cases. To rectify this, the Information Authority developed a case management database network that scheduled, tracked, and kept records of trials, decisions, and sentences. It also retained information on court costs, child support, fines, fees, and victim/witness information. The authority’s new database included a jury selection application and an application for public defenders to access files. By 1993, the Information Authority had articulated a vision of “judicial automation,” which revolved around linking court databases into the burgeoning network to streamline sentencing procedures. Data centralization posed unique difficulties for the courts at this point in time, as courts are reliant on information from a greater number of sources than corrections and law enforcement. Courts also depend on a greater variety of documents (e.g., decisions, filings, motions, stenographic transcriptions, tickets). The Information Authority thus looked to automated judicial databases in California and proposed a multifunctional, internet-based database for Illinois’s court system. Once implemented, the authority claimed, lawyers could use the newfound interoperability to transmit filings in both criminal and civil cases. The public could access the database through public terminals to view and pay traffic violations. The new database was to work in conjunction with the Criminal History Record Improvement Program, an initiative to set up an internet-based, interstate network of disposition and felon reporting. The goal of the program was to create a statewide criminal justice telecommunications system that would defray line charges accrued from the profusion of information.
The more punitive the city’s administration became, the more information its criminal justice system churned out. This was especially evident where indigent populations were criminalized. In 1996, the Department of Housing and Urban Development adopted its “one strike and you’re out” rule that banned many people with criminal records from public housing. About twenty-one thousand people reentered Chicago from prison, and half of the individuals in the city’s emergency centers had felony convictions. The Information Authority found that felonies reduced callbacks to job applications by 40 percent. The American Bar Association found that 1,449 Illinois statutes constricted felons’ rights, entitlements, and opportunities. The subsequent mass production of criminal justice data made data management the largest challenge to the Information Authority. Indeed, between 1984 and 1994, the total number of criminal records increased by 51 percent, which made the state’s criminal justice database system the fifth largest in the country. About two decades after launch, the total number of annual arrests entered into the database was 93 percent greater than the number entered in its first year. In its initial phase, about 60 percent of records in the CCH database came from Cook County, the county in which Chicago is located. By the end of the 1980s, this figure increased to 70 percent.
In mitigating this data eruption, the Illinois Sentencing Policy Advisory Council implemented a cost–benefit model that calculated recidivism probabilities to help determine candidates for early release. Database management systems in prisons were also linked to other databases throughout the state apparatus to speed up prisoner processing. Correctional Institution Management Information System (CIMIS) was one such example. One of the more striking features of CIMIS was its exploitation of the network form. Carceral technocrats declared that linking the database with the Information Authority’s wider network would cut the amount of time it took to book inmates in half. Such a network, they declared, would transmit data between correctional facilities and courts, medical institutions, police departments, and public and housing authorities for each inmate. This ability was said to enable administrators to cross-check inmate files with public aid files to determine eligibility for benefits while imprisoned. The database was also equipped with an accounting application to manage all money inmates possessed upon prison entry, the funds they received while incarcerated, and records of commissary transactions. CIMIS was also linked into the state’s Automated Fingerprint Identification System (AFIS), which processed between five hundred and six hundred characteristics per second. This was attributed to speeding up inmate processing and reducing fingerprint backlogs by nearly 60 percent. From 1993 to 1999, the number of fingerprints submitted to the database increased by 53 percent. To organize the profusion of biometric data, authorities turned to optical scanners and imaging software that took fingerprints directly from central booking or crime scenes, stored them in computer files, and transmitted them via the internet to CIMIS. It also matched fingerprints with state identification numbers, year of birth, and sex. Furthermore, AFIS afforded access to the Department of State Police’s fingerprint database, which stores fingerprint data taken from background checks on applications for certain purchases, licenses, and jobs.
What the Information Authority envisioned was a wirelessly connected punitive apparatus that could move the criminalized subject from point to point without interruption. This goal, untenable as it might be, led the state to take on massive projects to consolidate its criminal justice information via the web. Near the end of the century, the Information Authority teamed with the University of Illinois at Chicago faculty to upgrade criminal justice websites so that users could retrieve statistics from the state’s 102 counties. The authority produced and distributed its Criminal Justice Internet Applications Online Handbook to ensure that criminal justice websites followed standardized formats. Specifically, the handbook set the standards of CJHTM-L, an online discussion list for criminal justice webmasters; PoliceNet, a free web space for public safety agencies; and Spider Net, a law enforcement webmaster discussion list. The Automated Disposition Reporting Users Group—a committee of staff members from circuit court clerks’ offices, the Illinois Courts’ Administrative Office, the ISP, and the Secretary of State’s Office—also created a standardized data dictionary and electronic transmission format for exchanging information about court activities on the web.
Crowdsourcing the Patrol Function in Chicago
Inasmuch as the internet allows for the “extension of life as is,” it allows for the extension of racialized policing. The internet has been especially effective in dispersing modes of racialized profiling and control through the web and the public sphere. Of course, incident reporting phone lines have long existed and saw considerable expansion in the 1980s. Unlike emergency phone lines, however, the meshing of penal management and the web allows the state to mobilize large segments of the public sphere in real time.
In 1984, the state of Illinois’s Information Authority released its first proposal to make all criminal convict records publicly available. It was called the Criminal History Records Information (CHRI) Act. The proposal revisited many of the debates that surrounded the Freedom of Information Act (1977). Specifically, it explored the prospects of establishing statewide rules concerning public access to information about convictions. The CHRI Act made some of this information publicly available for a fee. Though arrest records that did not result in convictions were sealed by the act, information about people in custody or wanted persons was available for purchase. The final version of the bill was the product of contradictory objectives. For the Information Authority, “what we are debating is whether the government is going to do it . . . or whether private industry is going to do it.” For some representatives, the act was intended to establish control over the publicization of criminal justice statistics. For the Department of Law Enforcement, the CHRI Act did not revolve around the question of whether criminal history record information would become public. For law enforcement, the bill was an instrument to provide ways for civilians to offer information through mobile phones. Cellular phones were part of a new community-based strategy, Cellular Watch, organized by the National Crime Prevention Council and the electronics retailer Radio Shack. Cellular Watch was meant to provide channels for civilians to report crimes and suspicious behaviors. In addition to data entry, Illinois authorities moved to increase the public’s ability to retrieve criminal justice information. The Uniform Conviction Information Act (1991) mandated that all conviction information be made publicly available. Employers, landlords, private citizens, and licensing and investigative agencies were the presumed consumers of the information. The act precipitated a wave of public requests for criminal identification information. The same year the act passed, the ISP received 4,140 name requests and 499 fingerprint requests. In the span of just two years, the number of name requests rose by over 120 percent, and fingerprint requests increased by nearly 40 percent. Custodial care facilities, employers, rental agencies, and the U.S. Postal Service were among the most frequent customers.
“Information,” the CPD confidently declared a few years after passage of the Uniform Conviction Information Act, “is power. To support our new, decentralized approach to decisionmaking, the Department must establish a new, decentralized approach to data collection and analysis . . . to give officers the information they need, when and where they need it.” The CPD unveiled the first publicly accessible police database using Esri in 1995, the Information Collection for Automated Mapping (ICAM). Touted as a user-friendly digital mapping program for patrol officers and the public, it generated maps of CPD data according to beat, district, and sector. City officials held high-profile press conferences in police station houses to showcase police personnel and residents using the interface to plot buildings, churches, bars, liquor stores, pay phones, and schools identified as criminogenic by the machine. Much like CompStat, ICAM was presented to the public as a resource to cultivate networks of community patrols. It was developed alongside the Community Alternative Policing Strategy initiative, which designated civilians as a “new weapon in the fight against crime” and encouraged them to use ICAM to help police identify targets for patrol forces (see Figure 19). Thus, while ICAM was originally restricted to computer terminals in precinct stationhouses, it was extended to public kiosks and the web in 1996. ICAM was in many ways the technical expression of the city’s drive to revitalize and extend community policing earlier in the decade. For authorities in the 1990s, the success of community-based policing hinged on the efficient storage, retrieval, and utilization of publicly assessable information systems. Turning the public into an information source was also viewed as a means of diversifying department datasets and mobilizing local knowledge.
Despite ICAM’s arrival, the CPD remained far behind the curve in terms of capitalizing on the organizational opportunities afforded by internet technology. One such opportunity pertains to networking—the ability to continuously integrate additional nodes into the system. This inclusionist ideal of the internet, in which information flows freely, has a storied history that begins in earnest with the bulletin board system (BBS) movements in the late 1970s. These movements established the basic principles for social media networks, namely, the dream of a space where unfettered communication reigns. The radical implications of the BBS movement wouldn’t truly hit the CPD for three and a half decades. In 2005, the CPD and Local Initiatives Support Corporation undertook a ten-year program to create an online module for CLEAR. The program marked the first time a municipal police project was funded by the MacArthur Foundation. It was modeled after a statewide project a year prior to build an interdepartmental database network accessible to police throughout the state. Dubbed I-CLEAR, the network was the product of the combined labors of the CPD, ISP, and federal government. In Chicago, the CPD’s Information Services Division, consultants from Oracle Corporation, and faculty from the University of Illinois’s Department of Criminal Justice took lessons from I-CLEAR to design a similar network on the urban scale. City officials maintained that in making CLEAR publicly accessible, the new system, named CLEARpath, would breathe new life into community-based policing.
Initiatives to crowdsource CPD surveillance began to coalesce on the national scale during the time of CLEARpath’s arrival. In 2006, the governor of Texas awarded the Texas Border Sheriffs’ Coalition funds to build what turned out to be a network of military-grade surveillance cameras erected along the Rio Grande Valley section of the southern border. The network, which streamed video footage to the web in real time, was built by a tech firm that specializes in virtual community watch services. Users from around the planet are able to register as “virtual Texas deputies” and monitor the border, write reports, and send alerts to Border Patrol with the click of a button. This web-based surveillance apparatus, which introduced its own topology of administrative power, reached Chicago when CLEARpath was released five years later. Anyone with an internet connection could register to access CLEARpath, which enabled users to chart twenty-five blue-collar crimes and three white-collar crimes (forgery, fraud, embezzlement). It also came with tabs for mapping city services, gun offenders, narcotics activity, sex offenders, sex workers, troubled buildings, and civilian anticrime groups. It sent crime alerts, reports on gangs, and terrorist threat levels to its users. Registering for CLEARpath also gained users access to regular crime reports through emails, landlines, and text messages. It conveyed information on beat meetings, police districts, and police-sponsored events and allowed civilians to interact with the superintendent. CLEARpath also came equipped with a Crime Stoppers module that contained a gallery of wanted persons. Each photograph was formatted to be easily downloaded and converted into posters. Business, civilians, and community organizations can subscribe to receive posters of wanted persons. Crime Stoppers was linked to a phone line through which anonymous tippers could offer information to police for cash rewards. Another aspect of CLEARpath centered on giving the public opportunities to assist police in open cases. The public could assist police using CLEARpath through its anonymous Online Crime Reporting module. The module enabled the public to offer information on graffiti, harassment, lost property, property damage, simple assault, theft, and trespassing. Moreover, CLEARpath had a module for organizing, informing, and registering neighborhood watch groups to augment the surveillance of illicit markets.
The CPD’s networking capacity was given a veritable boost in 2014 by the Department of Homeland Security Office for Interoperability and Compatibility. The office coordinated efforts by the CPD, the Office of Emergency Management and Communications, and Purdue University’s Visual Analytics Center in a citywide program called Chicago Long-Term Evolution. Part of the program was dedicated to ensuring that the city could receive video data from the Nationwide Public Safety Broadband Network (NPSBN). Plans for NPSBN had been incubating since the onset of the War on Terror but gained considerable momentum through the Middle Class Tax Relief and Job Creation Act (2012). The act ultimately provided funding for FirstNet, a First Responder Network Authority housed in the Department of Commerce, which forged a public–private partnership with AT&T, General Dynamics, Inmarsat Government, Motorola Solutions, and Sapient Consulting to build and manage a $40 billion wireless broadband network.
From the perspective of the police apparatus, wireless networks were seen as a means of human dronification, the transformation of civic subjects into a flexible configuration of sentinels. The extension of police surveillance through wireless networks echoes Foucault’s analysis of the police surveillance’s tendency toward generalization, as the police apparatus had to be given the instrument of “permanent, exhaustive, omnipresent surveillance” and fueled by “unceasing observation . . . accumulated in a series of report and registers.” However, it is important to stress the fact that police surveillance and its network of human drones are tools of social management designed explicitly for minorities who are cast to the margins of the civic sphere.
Seeing Like a Police State
The democratization of police data allows for the democratization of racialized policing. While New York City trailed Chicago in exploring the full potential of making police datasets available on the internet, it quickly realized what could be gained. Much like the community policing ideology that helped bring ICAM into existence in Chicago, the NYPD’s online crime mapping application, CompStat 2.0, was touted by officials as an instrument of community-based policing. In point of fact, the NYPD’s move to create an online portal to its incident report system was catalyzed by mounting antagonisms between the police and black and latinx communities. The relations grew especially explosive following the 2014 murder of Eric Garner, an unarmed man killed for selling cigarettes without tax stamps. Mayor Bill de Blasio (2014–) presented the act of putting the department’s incident information online as an olive branch of sorts. The mayor insisted that the online database would improve governmental transparency. Unveiled on CompStat’s twenty-first birthday, version 2.0 gave the public access to unprecedented amounts of information from NYPD databases. It came equipped with a data visualization engine that enabled users to make charts, graphs, and maps of reported incidents by date and time of day. Whereas the first installment of CompStat geocoded crime events at the scale of the precinct, version 2.0 geocoded them at the scale of the street address.
One of CompStat 2.0’s less apparent functions was creating a virtual community to extend the NYPD’s environmental awareness. In some ways, forging community groups to augment NYPD surveillance was nothing new. Since the early 1940s, the NYPD has organized precinct community councils (originally called precinct coordinating councils) to give civilians opportunities to express local concerns and provide police with local insights. But with CompStat 2.0, the NYPD took the concept of councils to cyberspace. Like precinct community counsel meetings, CompStat 2.0 provided the public with opportunities to transmit information to police. And like these councils, CompStat 2.0 was designed to perform a community-building function. But whereas precinct community councils forged local networks, CompStat 2.0 forged citywide networks. In fact, CompStat 2.0 was viewed more than seventy-five thousand times in its opening week. It was regarded by the city as a smashing success. Online magazines lauded the application that “looks a little like Yelp, but for grand larceny” and provides a “weirdly fun way of poking around the city.” CompStat 2.0 was effectively created to fuse police subjectivity with public subjectivity. Its ultimate product would be a digitized intersubjectivity that monitored, interpreted, articulated, and even experienced urban space from the tactical viewpoint of police. CompStat 2.0 was like a virtual reality headset that enabled the public to see like a police state.
This process, where administrative power wields wireless networks to reinforce its exclusionary practices, was captured in an episode of the anthology film series Black Mirror titled Men against Fire. The episode centers on a military organization in Denmark tasked with liquidating a group of untouchables. The organization gives each soldier a neural implant called MASS, which enables the former to control the latter’s sensory inputs and situational awareness. The implant enhanced soldier conditioning, communication, firearm accuracy, and intelligence by augmenting their cognition with ballistics data, drone feeds, suspect profiles, simulated memories, and three-dimensional maps. But its most important attribute was that it suppressed empathy by blocking each soldier’s ability to properly hear, see, or smell the untouchable population. In the end, we learn the true identities of the untouchables: they are people identified to be at higher risks of cancer, criminal tendencies, low intelligence quotient scores, multiple sclerosis, muscular dystrophy, sexual deviances, and Sjogren–Larsson syndrome. MASS implants did not only help soldiers identify these untouchables but also inflict violence upon them with good conscience. Similar to Men against Fire, then, CompStat 2.0 involves racialized administrative power operating under a pretext of public safety. CompStat 2.0 digitally represents the most heavily stigmatized populations of New York City as objects of differential supervision and punishment. CompStat 2.0 reflects how the state attempts to administer what American studies theorist Chandan Reddy terms subjectivity practices. These practices, which have been intensified following the explosive social contradictions of the late 1960s, are characterized by increased efforts on behalf of the state to mobilize racially heterogeneous populations to defray costs of the racialized violence required of capital accumulation. With CompStat 2.0, minorities from the most heavily marginalized communities are enjoined to aid the police apparatus in crime-reduction initiatives. In the end, the CompStat 2.0 website is a technology developed with latent ambitions to convert the diverse public into a homogenous appendage of the NYPD. Practically speaking, it was designed to cultivate virtual communities of additional eyes and ears for the police.
The democratization of criminal justice data went hand in hand with the antidemocratic essence of mass criminalization. The spread of the data across the web brought penal populism into the internet age. In 2013, the city launched its Data Analytics Recidivism Tool (DART), the first web-based application to track and analyze the seventy-five thousand individuals rearrested each year. The first of its kind in the country, DART compiles data on rearrests for criminal, felony, and violent offenses. It stores the age, arraignment recommendations, borough, charges, desk appearance tickets, dispositions, gender, open cases, prior convictions, and sentences of these recidivists. DART was launched under the pretenses of data democratization and governmental transparency and was said to empower civic groups, journalists, and researchers. Perhaps the most perverse permutation of NYPD networking was initiated by the police union, the Sergeant’s Benevolent Association. Two years after DART was launched, the union’s president issued an antihomeless open letter to the public in reaction to gains made by police reform activists and the City Council. The letter called the reform demands following Eric Garner’s murder the work of “inept and spineless public officials” engaged in self-interest, self-promotion, and self-aggrandizement. The letter implored New Yorkers to photograph homeless people, panhandlers, and quality-of-life offenders and email the photographs to the union, which it posted on a Flickr account. The vitriolic focus on homeless people reflected the extent to which the police had morphed into an apparatus whose prime objective was to manage the collateral damage of urban restructuring. So entrenched in this hateful enterprise was the union that it sought to mobilize the public to spread the stigma of poverty via the web.
Weaving the Penal Web
In Neal Stephenson’s novel Diamond Age, the primary technology of urban security consisted of airborne pods the size of ping-pong balls that floated throughout the city. The pods were programmed to “hang in space in a hexagonal grid pattern, about ten centimeters apart near the ground . . . and spaced wider as they got higher. . . . When the wind gusted, the pods swung into it like weather vanes, a grid deformed for a bit as the pods were shoved around; but all of them eventually worked their way back into place, swimming upstream like minnows, propelling the air turbines.” One of the core functions of the pod grid was to maintain territorial order. They were deployed to establish borders and monitor the sights and sounds on the street. Individuals could walk through the floating grid simply by pushing some pods out of the way—that is, “unless Royal Authority had told the pods to electrocute you or blast you.” This established a mobile meshwork of surveillance and capture, which maintained sociospatial divisions within and around the city.
The faintly visible yet profound extension of penal web technology is making Stephenson’s description appear more realistic. While today’s mobile smart devices allow the penal state to mobilize ordinary civilians as its eyes and ears, future web technologies such as intelligent agents, the Internet of Things (IoT), and semantic tagging establish conditions for something different. In 2014, the National Institute of Justice and RAND Corporation convened an expert panel to explore how new web technologies could be harnessed by the penal state. Part of the panel revolved around brainstorming how Web 2.0 technologies could be used. Whereas Web 1.0 technologies are designed primarily for linking documents over the internet (e.g., hypertextual protocol or TCP/IP), Web 2.0 technologies are designed for social networking and crowdsourcing. Social network analysis is one methodology to grow out of Web 2.0. In criminal justice, this methodology manifested in algorithms sent to probe the web for signs of future criminal activity. More than four hundred law enforcement agencies conduct social media surveillance in some way or another. The NYPD began monitoring the social media activity of hundreds of youths in “proto-gangs,” some of whom were as young as ten years of age. A variety of social media intelligence platforms have been developed by technology corporations to find criminogenic signals in online activity. The corporations are numerous: for instance, Dataminr in New York; Digital Stakeout in Atlanta, Georgia; Media Sonar Technologies in Ontario; Snaptrends in Austin, Texas; or TransVoyant in Alexandria, Virginia. Geofeedia, a firm whose social media surveillance software was partially funded by the Central Intelligence Agency, mines geolocation data, images, and screen names from Periscope, YouTube, Twitter, and other common social media apps. In Baltimore, demonstrators protesting police officers Caesar R. Goodson, Garrett E. Miller, Edward M. Nero, William G. Porter, and Lieutenant Brian W. Rice’s merciless killing of Freddie Gray were identified through social media surveillance through search terms including basic Arabic words, #BlackLivesMatter, #MuslimLivesMatter, and “protest.”
The apparatchiks of the American penal state have also shown interest in consolidating criminal justice information through cloud computing. “If the commercial model holds true in the law enforcement world,” Integrated Justice Information Systems Institute researchers concluded in 2012, “then it is reasonable to expect that the largest agencies might be attracted to the construction of their own private cloud.” Cloud computing is delivered through various service models characterized by varying levels of user control over applications, operating systems, servers, storage, and systems platforms. The key advantage of these services is that they dramatically lower the cost of data storage and retrieval. As they became more prevalent in the private sector, the Bureau of Justice Assistance stressed that cloud services were becoming necessary due to the rapid growth of criminal justice data generated by networks of audio sensors, body cameras, environmental sensors, and surveillance cameras. The IACP similarly recognized cloud computing as a means to respond to increased demands on storage prompted by the implementation of body cameras and other sensory devices.
Technologists of mass punishment have also promoted cloud computing as a means to manage the strain on data storage. For instance, as the Illinois Department of Corrections found its facilities were overpopulated by nearly fifteen thousand people, it was forced to increase parole programs that took in data from counselors, psychiatrists, medical doctors, and supervisors. The state’s chief of information technology policy and planning implored lawmakers to provide data storage upgrades, which arrived in the form of Microsoft Dynamics Customer Relation Management Online cloud service. In 2010, the National Archives and Records Administration mandated that all federal agencies begin to adopt cloud computing services. The National Institute of Standards and Technology established standards and guidelines for the project. Shortly thereafter, the FBI mandated that all cloud technologies sold to U.S. law enforcement agencies comply with CJIS standards. The CJIS Group, which was bought by Curran Companies, was pivotal in facilitating the transition in state agencies and the IT sector. This grand standardization project created new opportunities for IT businesses. Amazon Web Services (AWS) announced its compliance with CJIS standards and nestled its way into this emerging market niche. In fact, the AWS Cloud is now used in a wide spectrum of enforcement services for everything from storing data on citations, incidents, and reports in real time to boost officer productivity, to forensic data for evidence-tracking systems, to “situational awareness video” data from body camera feeds.
Penal experts have scouted Web 3.0 technologies, where data can be searched using natural language. This enables digital devices to “understand” the content of data and information and communicate it to humans in spoken and written language. The NIJ and RAND Corporation has proposed exploiting this technology to automate the surveillance of former offenders’ activities and social connections, inmate phone calls, offender locational data, and online money exchanges. Penal bureaucrats have also sought to supplement semantic technologies with Web 4.0 and the IoT, which links erstwhile “dumb” objects into the web so that they can be monitored and manipulated continuously and from afar. IoT also makes objects and surfaces interfaces for web browsers, which renders material environments conduits for information flows. In the criminal justice field, one possible application of IoT technology is wearable biomedical sensors to monitor alcohol and drug use of people under supervision. Another involves virtual police badges with proximity sensors to enhance patrol units’ awareness of where other units are located to synchronize their movements. The federal government and technology firms have explored the feasibility of IoT-enabled aerial drones and driverless vehicles to keep watch over roads, public squares, and targeted communities; facial recognition systems capable of searching though all mug shot databases; tools capable of extracting structured data from narrative descriptions in incident reports; and virtual courtroom video teleconferencing kits that could eliminate court visits in some cases.
But what does all this mean for penal governance? What might such potentially radical levels of decentralization mean for the punitive management of criminalized populations? As 2015 rolled around, almost 20 million people had felony records, and up to 100 million people had criminal records of some sort. The American Bar Association’s National Inventory of the Collateral Consequences of Conviction lists more than forty-eight thousand administrative penalties, laws, and regulations that constrain the mobility of people with felony records. These records restrain access to housing markets, labor markets, and public welfare agencies. The meshing of the penal state and the web means that these records can be automatically retrieved in any official dealings with private and public institutions that use computers. This state of affairs establishes conditions for a truly millennial mode of punishment, characterized by extreme shaming, ostracism, and embarrassment, which are all backed by the administrative state’s apparatuses of violence. Perhaps more frighteningly, the penal state’s embrace of the network form through the web gives rise to new vectors of penal populism. Networks are decentralized, relatively centerless. They flourish by devolving and/or subtracting power centers and replacing them with provisional command posts. They cannot be identified with reference to any single point. Insofar as we can identify a “system” to emerge from network logics, it is a swarm system, consisting of local actors communicating in global networks. During ordinary times, each node’s capacity to contribute to networks lies dormant. But it can be instantly activated by another node in close proximity or a command post from afar. The rise of punitive web technology maintains the situation in which the negatively racialized poor can remain in cities, but they must remain apart from their centers of conspicuous consumption, labor markets, leisure, residences, and wealth. The web-based networks of punishment ensnare criminalized subjects in something like a low-intensity form of Agamben’s state of exception, where violence and legal authority meet and mesh to strip away the subject’s civic persona. Indeed, digitized penal stigma facilitates differential access to capital, labor markets, and physical liberty on the part of criminalized populations. However, what today’s networks of racial punishment demonstrate is that this state is anything but exceptional.