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Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor by Virginia Eubanks
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“We all live in the digital poorhouse. We have always lived in the world we built for the poor. We create a society that has no use for the disabled or the elderly, and then are cast aside when we are hurt or grow old. We measure human worth based only on the ability to earn a wage, and suffer in a world that undervalues care and community. We base our economy on exploiting the labor of racial and ethnic minorities, and watch lasting inequities snuff out human potential. We see the world as inevitably riven by bloody competition and are left unable to recognize the many ways we cooperate and lift each other up.

But only the poor lived in the common dorms of the county poorhouse. Only the poor were put under the diagnostic microscope of scientific clarity. Today, we all live among the digital traps we have laid for the destitute.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Our national journey from the county poorhouse of the nineteenth century to the digital poorhouse today reveals a remarkably durable debate between those who wish to eliminate and alleviate poverty and those who blame, imprison, and punish the poor.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“When automated decision-making tools are not built to explicitly dismantle structural inequities, their speed and scale intensify them.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Oath of Non-Harm for an Age of Big Data I swear to fulfill, to the best of my ability, the following covenant: I will respect all people for their integrity and wisdom, understanding that they are experts in their own lives, and will gladly share with them all the benefits of my knowledge. I will use my skills and resources to create bridges for human potential, not barriers. I will create tools that remove obstacles between resources and the people who need them. I will not use my technical knowledge to compound the disadvantage created by historic patterns of racism, classism, able-ism, sexism, homophobia, xenophobia, transphobia, religious intolerance, and other forms of oppression. I will design with history in mind. To ignore a four-century-long pattern of punishing the poor is to be complicit in the “unintended” but terribly predictable consequences that arise when equity and good intentions are assumed as initial conditions. I will integrate systems for the needs of people, not data. I will choose system integration as a mechanism to attain human needs, not to facilitate ubiquitous surveillance. I will not collect data for data’s sake, nor keep it just because I can. When informed consent and design convenience come into conflict, informed consent will always prevail. I will design no data-based system that overturns an established legal right of the poor. I will remember that the technologies I design are not aimed at data points, probabilities, or patterns, but at human beings.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“America's poor and working-class people have long been subject to invasive surveillance, midnight raids, and punitive public policy that increase the stigma and hardship of poverty. During the nineteenth century, they were quarantined in county poorhouses. During the twentieth century, they were investigated by caseworkers, treated like criminals on trial. Today, we have forged what I call a digital poorhouse from databases, algorithms, and risk models. It promises to eclipse the reach and repercussions of everything that came before.

Like earlier technological innovations in poverty management, digital tracking and automated decision-making hid poverty from the professional middle-class public and give the nation the ethical distance it needs to make inhuman choices: who gets food and who starves, who has housing and who remains homeless, and which families are broken up by the state. The digital poorhouse is part of a long American tradition. We manage the individual poor in order to escape our shared responsibility for eradicating poverty.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Marginalized groups face higher levels of data collections when they access public benefits, walk through highly policed neighborhoods, enter the health-care system, or cross national borders. That data acts to reinforce their marginality when it is used to target them for suspicion and extra scrutiny. Those groups seen as undeserving are singled out for punitive public policy and more intense surveillance, and the cycle begins again. It is a kind of collective red-flagging, a feedback loop of injustice.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“The digital poorhouse is persistent. Once they scale up, digital systems can be remarkably hard to decommission. Think, for example, about what might happen if the world learned about a gross violation of trust at a large data company like Google.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“But its outwardly neutral classifications mask discriminatory outcomes that rob whole communities of wealth, compounding cumulative disadvantage.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“New high-tech tools allow for more precise measuring and tracking, better sharing of information, and increased visibility of targeted populations. In a system dedicated to supporting poor and working-class people's self-determination, such diligence would guarantee that they attain all the benefits they are entitled to by law. In that context, integrated data and modernized administration would not necessarily result in bad outcomes for poor communities. But automated decision-making in our current welfare system acts a lot like older, atavistic forms of punishment and containment. It filters and diverts. It is a gatekeeper, not a facilitator.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“While poorhouses have been physically demolished, their legacy remains alive and well in the automated decision-making systems that encage and entrap today's poor. For all their high-tech polish, our modern systems of poverty management - automated decision-making, data mining, and predictive analysis - retain a remarkable kinship with the poorhouses of the past. Our new digital tools spring from punitive, moralistic views of poverty and create a system of high-tech containment and investigation. The digital poorhouse deters the poor from accessing public resources; polices their labor, spending, sexuality, and parenting; tries to predict their future behavior; and punishes and criminalizes those who do not comply with its dictates. In the process, it creates ever-finer moral distinctions between the 'deserving' and 'undeserving' poor, categorizations that rationalize our national failure to care for one another.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Poverty is denied by the media and political commentators, who portray the poor as a pathologically dependent minority dangerous to professional middle-class society. This is true from both conservative and liberal perspectives: voices from the Right tend to decry the poor as parasitic while voices from the Left paternalistically hand-wring about the poor’s inability to exert agency in their own lives.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“The cheerleaders of the new data regime rarely acknowledge the impacts of digital decision-making on poor and working-class people. This myopia is not shared by those lower on the economic hierarchy, who often see themselves as targets rather than beneficiaries of these systems. For example, one day in early 2000, I sat talking to a young mother on welfare about her experiences with technology. When our conversation turned to EBT cards, Dorothy Allen said, “They’re great. Except [Social Services] uses them as a tracking device.” I must have looked shocked, because she explained that her caseworker routinely looked at her purchase records. Poor women are the test subjects for surveillance technology, Dorothy told me. Then she added, “You should pay attention to what happens to us. You’re next.” Dorothy’s insight was prescient. The kind of invasive electronic scrutiny she described has become commonplace across the class spectrum today. Digital tracking and decision-making systems have become routine in policing, political forecasting, marketing, credit reporting, criminal sentencing, business management, finance, and the administration of public programs. As these systems developed in sophistication and reach, I started to hear them described as forces for control, manipulation, and punishment”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Across the country, poor and working-class people are targeted by new tools of digital poverty management and face life-threatening consequences as a result. Automated eligibility systems discourage them from claiming public resources that they need to survive and thrive. Complex integrated databases collect their most personal information, with few safeguards for privacy or data security, while offering almost nothing in return. Predictive models and algorithms tag them as risky investments and problematic parents. Vast complexes of social service, law enforcement, and neighborhood surveillance make their every move visible and offer up their behavior for government, commercial, and public scrutiny”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Automated decision-making shatters the social safety net, criminalizes the poor, intensifies discrimination, and compromises our deepest national values. It reframes shared social decisions about who we are and who we want to be as systems engineering problems. And while the most sweeping digital decision-making tools are tested in what could be called “low rights environments” where there are few expectations of political accountability and transparency, systems first designed for the poor will eventually be used on everyone.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“From the beginning, the poorhouse served irreconcilable purposes that led to terrible suffering and spiraling costs. On the one hand, the poorhouse was a semi-voluntary institution providing care for the elderly, the frail, the sick, the disabled, orphans, and the mentally ill. On the other, its harsh conditions were meant to discourage the working poor from seeking aid. The mandate to deter the poor drastically undercut the institution’s ability to provide care. Inmates were required to swear a pauper’s oath stripping them of whatever basic civil rights they enjoyed (if they were white and male). Inmates could not vote, marry, or hold office. Families were separated because reformers of the time believed that poor children could be redeemed through contact with wealthy families. Children were taken from their parents and bound out as apprentices or domestics, or sent away on orphan trains as free labor for pioneer farms. Poorhouses provided a multitude of opportunities for personal profit for those who ran them. Part of the keeper of the poorhouse’s pay was provided by unlimited use of the grounds and the labor of inmates.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Scientific charity workers advised in-depth investigation of applications for relief because they believed that there was a hereditary division between deserving and undeserving poor whites. Providing aid to the unworthy poor would simply allow them to survive and reproduce their genetically inferior stock. For middle-class reformers of the period, like scientific social worker Frederic Almy, social diagnosis was necessary because “weeds should not have the same culture as flowers.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Like earlier technological innovations in poverty management, digital tracking and automated decision-making hide poverty from the professional middle-class public and give the nation the ethical distance it needs to make inhuman choices: who gets food and who starves, who has housing and who remains homeless, and which families are broken up by the state. The digital poorhouse is part of a long American tradition. We manage the individual poor in order to escape our shared responsibility for eradicating poverty.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“In the Buck v. Bell case that legalized involuntary sterilization, Supreme Court Justice Oliver Wendell Holmes famously wrote, “It is better for all the world if, instead of waiting to execute degenerate offspring for crime or to let them starve for their imbecility, society can prevent those who are manifestly unfit from continuing their kind. The principle that sustains compulsory vaccination is broad enough to cover cutting the Fallopian tubes.”11 Though the practice fell out of favor in light of Nazi atrocities during World War II, eugenics resulted in more than 60,000 compulsory sterilizations of poor and working-class people in the United States.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“New Deal legislation undoubtedly saved thousands of lives and prevented destitution for millions. New labor laws led to a flourishing of unions and built a strong white middle class. The Social Security Act of 1935 established the principle of cash payments in cases of unemployment, old age, or loss of a family breadwinner, and it did so as a matter of right, not on the basis of individual moral character. But the New Deal also created racial, gender, and class divisions that continue to produce inequities in our society today. Roosevelt’s administration capitulated to white supremacy in ways that still bear bitter fruit. The Civilian Conservation Corps capped Black participation in federally supported work relief at 10 percent of available jobs, though African Americans experienced 80 percent unemployment in northern cities. The National Housing Act of 1934 redoubled the burden on Black neighborhoods by promoting residential segregation and encouraging mortgage redlining. The Wagner Act granted workers the right to organize, but allowed segregated trade unions. Most importantly, in response to threats that southern states would not support the Social Security Act, both agricultural and domestic workers were explicitly excluded from its employment protections. The “southern compromise” left the great majority of African American workers—and a not-insignificant number of poor white tenant farmers, sharecroppers, and domestics—with no minimum wage, unemployment protection, old-age insurance, or right to collective bargaining.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“As backlash against welfare rights grew, news coverage of poverty became increasingly critical. “As news stories about the poor became less sympathetic,” writes political scientist Martin Gilens, “the images of poor blacks in the news swelled.”17 Stories about welfare fraud and abuse were most likely to contain images of Black faces. African American poverty decreased dramatically during the 1960s and the African American share of AFDC caseloads declined. But the percentage of African Americans represented in news magazine stories about poverty jumped from 27 to 72 percent between 1964 and 1967.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“A combination of restrictive new rules and high-tech tools reversed the gains of the welfare rights movement. In 1973, nearly half of the people living under the poverty line in the United States received AFDC. A decade later, after the new technologies of welfare administration were introduced, the proportion had dropped to 30 percent. Today, it is less than 10 percent.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Millions of copies of drivers’ licenses, social security cards, and other supporting documents were faxed to a centralized document processing center in Grant County; so many of them disappeared that advocates started calling it “the black hole in Marion.” Each month the number of verification documents that vanished—were not attached properly to digital case files in a process called “indexing”—rose exponentially. According to court documents, in December 2007 just over 11,000 documents were unindexed. By February 2009, nearly 283,000 documents had disappeared, an increase of 2,473 percent. The rise in technical errors far outpaced increased system use. The consequences are staggering if you consider that any single missing document could cause an applicant to be denied benefits.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“Containment in the physical institution of a county poorhouse had the unintentional result of creating class solidarity across race, gender, and national origin. When we sit at a common table, we might see similarities in our experiences, even if we are forced to eat gruel. Surveillance and digital social sorting drive us apart as smaller and smaller microgroups are targeted for different kinds of aggression and control. When we inhabit an invisible poorhouse, we become more and more isolated, cut off from those around us, even if they share our suffering.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“The digital poorhouse is hard to understand. The software, algorithms, and models that power it are complex and often secret. Sometimes they are protected business processes, as in the case of the IBM and ACS software that denied needy”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
“The digital poorhouse is massively scalable. High-tech tools like automated decision-making systems, matching algorithms, and predictive risk models have the potential to spread very quickly.”
Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor