(I received a free copy of this book from Net Galley in exchange for an honest review.)

A powerful investigative look at data-based discrimination—and how technology affects civil and human rights and economic equity
The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years—because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect.
Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor.
In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile.
The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values.

What a magnificent book. As scary as it is fascinating, this books looks at the way politicians and other agencies use technology, rather than human interaction, to decide who needs help and assistance in society.

The author takes up three studies in this book: the healthcare system, homelessness and child welfare. The author takes us to three cities around the country - Indiana, Los Angeles, and Pittsburgh. Three completely different locations but each with a similar problem: the use of certain technologies, algorithms and statistical manipulation to assist those in authority to decide who is "in need" for assistance. Problem is, of course, that these automated systems are never foolproof, are never in touch with humans, and are impossible to argue with.

The background to each location/issue was very welcomed - especially the history of poor houses in the US. I found that fascinating and immediately after finishing the book, I went in search for more about this subject. The history of Skid Row was also curious - the way politics and development affected the lives of those living there. The research into not just the main topics, but also the histories, was brilliant. I was truly in awe of the information included in this book.

The one thing that stopped me from giving this 5-stars was that it was very repetitive - especially with the keywords for the subject. I couldn't tell you how many times I read the phrases: data mining, predictive risk and policy algorithms, to name just a few. It got to be a bit much at times and did reduce my enjoyment a little bit.


Paul
ARH

A copy of this title has been provided by the publisher via NetGalley in exchange for an honest review.

‘Automating Inequality’ explores the current state of public assistance programs in the United States through 3 fascinating case studies...a disastrous automated benefits eligibility system in Indiana, The coordinated entry system for the unhoused in L.A. that mines large volumes of sensitive data and leaves many falling through the cracks, and an attempt to predict child abuse in Allegheny County that sounds like a Philip K. Dick premise. Eubanks also provides a thorough look at the history of American policies against the poor...from the physical poorhouse to the digital poorhouse. Overall, the argument for exercising caution against these automated programs recognizes the nuance of the human condition while urgently warning against algorithms that merely serve as extensions of structural discrimination against the poor. An important read for data nerds, privacy geeks, policy makers, activists, and anyone interested in what it means to be poor in America.

‘Automating Inequality’ is available now through your local library and booksellers big and small.

Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor by Virginia Eubanks is a report on the use of technology in determining government assistance programs. This is a detailed, highly researched report on how the digital age is used to punish America's poor and low income. As a former social worker I found it very true to fact as well as shocking. If your not in the 1% of the privileged in this country you must read this book. Beware should you need government assistance this will outline the ways in which American counties are denying those in need and punishing them for what is perceived as their errors but is in fact digital control over each states' number of applications, history and needs assessments. With this digital control you will find out why millions are denied rightful benefits and are suffering. I found this a must read subject but be warned it is shocking and disturbing how much control the government has over our lives .This will shock you to your core.
I received a ARC which did not influence my review.

The amount of personal information floating around in the electronic world is staggering. In Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor, Virginia Eubanks argues that we have created an electronic poor house, with "automated decision-making systems [which] shatter the social safety net, criminalize the poor, intensify discrimination, and compromise our deepest national values." Lest her readers think this only applies to the poor and not their own educated, middle-class selves, she adds, "systems first designed for the poor will eventually be used on everyone."


Eubanks, a political science professor, examines a few very specific systems used in agencies which serve the poor: an Indiana program which sorts data for welfare eligibility, a Los Angeles program which identifies homeless clients for housing programs and services, and a Pittsburgh program for child and family services. Each has been touted as improving efficiency, reducing fraud, and reducing waste.


Eubanks isn't much of a fan of any of these programs, or others like them. A big, obvious problem is the possibility that "all that data is being held for other purposes entirely: to surveil and criminalize" the poor. In some instances, law enforcement has accessed data from these systems to track people down and run sting operations. In others, officials extrapolate data to anticipate issues and preemptively intervene in family's lives. Eubanks calls this "poverty profiling."


For Eubanks, the root problem is that these systems don't address the root problems of poverty. They reveal a historical pattern in which "during times of economic hardship, America's elite threw the poor under the bus." It continues today, but now "they are handing the keys to alleviating poverty over to a robotic driver." Her solution would be to dismantle the electronic data and surveillance systems and establish the universal basic income, which is simply a cash transfer program. As socialistic as this sounds, her argument is certainly sound, and by reducing or eliminating welfare bureaucracies it could conceivably work. Wouldn't you rather a few thousand of your federal government's dollars go to a needy family rather than a electronic data tracking system?


Eubanks offers terrific insight from her extensive observations in these three programs. It's downright scary to see how much of our information is mined for use by government agencies. The Pittsburgh program identifying potential future child abusers is particularly troubling. Automating Inequality is an important read for people concerned about the future of government services for the poor as well as the future (and present!) of government surveillance of individual Americans.


Thanks to NetGalley and the publisher for the complimentary electronic review copy!

Virginia Eubanks has done all of us a favor, and we should really appreciate how difficult this must have been. She looks at a large stretch of American history, in how it treats its poor and oppressed minority groups and uses technology to do so. This is not an easy or pleasant thing to come to grips with, but Ms. Eubanks does it with this very readable and succinct volume. She leaves nothing out and brings us to an overall understanding of what has occurred and the general direction.

Everyone will have their own point of view on this. Ms. Eubanks provides ample information both statistical and anecdotal for you to develop your own ideas as to how this menace must be confronted. For me the sheer waste of funds only used to create division and poverty is staggering. Simply treating people with dignity would save money and hardship for everyone. The system to provide assistance is used to control, oppress and perpetuate needless misery. We need people to have the money they need to survive and stop governments and the rich acting like childish bullies to those in greatest need.

Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor by Virginia Eubanks is a report on the use of technology in determining government assistance programs. Eubanks is the co-founder of Our Knowledge, Our Power (OKOP), a grassroots anti-poverty and welfare rights organization, and is Associate Professor in the Department of Women's Studies at the University at Albany, SUNY.

Public assistance programs are seen as a drag on the economy to many people.  People work hard for their money don't want to see their tax dollars abused.  Reagan exaggerated stories of welfare queens.  The 1970s were filled with images of Caddilac's parked in front of welfare offices.  Public assistance is typically seen as an abused system.  The good that it does is under-reported when compared to the abuse.  

Over seventy percent of full-time workers say they live paycheck to paycheck.  The average American also has nearly $16,000 in credit card debt.  For those seeking an education, student loan debt piles up faster than job opportunities.  Many Americans are balancing on the edge of homelessness and bankruptcy.  

Eubanks looks at three separate areas in three different parts of the country and examines what automation has done in determining benefits and the problems it causes. Poverty in America is real and a growing problem.  We see it every day and do our best to block it out.  Americans also have a history of moving away from poverty -- out of the cities and into the suburbs and back again.  

The first area Eubanks describes is automation and privatization of public services to save money and limit fraud (which is very small).  Applications are done over the phone to a call center (which was problematic for the deaf) or online.  In poor areas, libraries and librarians are overrun trying to provide internet service to patrons filing for benefits.  In one case (years ago, I imagine) a woman added the food stamps phone number to her family and friends list because she spent so much time on the phone with them over benefits.  When Indiana automated it was a disaster.  Call centers and document centers did not follow through on paperwork many lost benefits for failure to cooperate when paperwork was lost.  This was life-threatening to many on medication.  Fixing problems was met with resistance, paperwork, and delays. 

Skid Row in Los Angeles became the defacto homeless area.  Keeping a defined area homelessness helped insulate the public from the homeless.  Gentrification, however, pushed the homeless out of their "home."  Arrests for sitting or laying on the sidewalk, confiscation of property, and basically criminalizing homelessness became the government's solution.  In Pennsylvania, Child Services uses an algorithm to predict future behavior.  Vendetta calls remain in the parent's/child's records.  In both cases, algorithms have taken over for human interaction and understanding.  Computers take certain answers but most of the time no matter what is being filled out "Other" is filled out especially when something as important as physical and mental health.  Computers are poor interpreters of "other." 

Automating Inequality demonstrates the problems of algorithms and automation and what it does identify the poor and many cases work to keep the poor poor.  The system was intended to provide assistance for the short term and help people out of poverty has become a system to perpetuate poverty.  An interesting report based on real-life examples and real-life workers.

Target, track, punish. Repeat.

Notwithstanding what the French wrote on the Statue of Liberty, America hates its poor. It will spend billions to deny them help. In Automated Inequality, Virginia Eubanks says we manage the poor so we don’t have to eradicate poverty. Instead, we have developed a Digital Poorhouse – high tech containment of the poor and recording of their every action, association and activity. The great innovation today is the prediction model, using the child, the parents, neighbors and even the neighborhood to predict when a child should be removed and given to foster care – before anything has happened.

America’s war against its poor goes back some 200 years. It has put them in poorhouses and debtors’ prisons, made it difficult or impossible for them to live freely and raise a family, denied them benefits set out in law, sterilized them, and contemplated encouraging them to just die. The latest iteration is high tech. Government tracks the movements, purchases, and habits of those unfortunate enough to seek its help. It’s all automated. Decisions are made by algorithms, and undoing the ensuing mess is somewhere between exasperating and impossible. Eubanks explores three very different and widely separated approaches to managing, manipulating and controlling the poor in Indiana, the homeless in Los Angeles, and the child welfare in Pittsburgh.

-During the financial crisis, when millions lost jobs and homes, Indiana actually reduced the percentage of the legally poor on welfare from 38% to 8. It hired IBM to centralize all activity, including document collection. Local caseworkers disappeared, becoming call center agents. They were measured on productivity – how little time they spent with applicants. The slightest error in the 30 document process meant instant automatic denial of benefits. Applicants received a notice of “Failure to co-operate” with no explanation whatsoever. This could include failure to answer the phone for an interview the system rescheduled without notice, failure sign in the numerous places required, and failure of the system to scan and enter the documents submitted. One woman was confined to a hospital bed when they called her home. She was immediately cut off from all benefits, including Medicaid for her cancer, free transport to medical appointments, and foods stamps. They day after she died, she won her appeal.

-Los Angeles has worked hard to gentrify Skid Row. Rather than allow renovation, it has actually removed more housing than there are homeless there. Rumors of the availability of a room can cause lineups for days. LA has spent $11 million collecting data on individuals, but almost all are still homeless. It has been an exercise in tracking and surveillance, with ever more intrusive questionnaires and interviews, mental health tests, and essentially no hope of permanent placement. But everyone goes through the process, often several times, providing intimate details to be used against them. Police apply huge pressure to get the poor out of there, adding to their life records. In 2006, they made 9000 arrests and 12,000 citations in an area with a population of maybe 15,000.

-Allegheny County (Pittsburgh) has a data warehouse of every contact anyone has ever had with public services, including data like the date, amount and location of every purchase with a welfare card. It’s an average of 800 pieces of information per person. Algorithms decide if children are at risk of abuse or neglect. The error rate for both false positives and false negatives is high, putting children, and their parents, at risk. Naturally, an outsized percentage of cases involve those who are poor and black. But the reality is that most of the children investigated are not physically or sexually abused. They are poor.

Eubanks rails against us looking the other way, being indifferent, fearing for our own status, and other such liberal guilt. It makes the book end badly. It detracts from the premise that big data is taking over entire lives, keeping people in their place and preventing the help lawmakers prescribe. The blame needs to stay at the top, even if the solution might come from the bottom.

The punchline in all these scenarios is that poverty costs more money than it’s worth. President Nixon saw this in the late 60s. He proposed a national basic income. With money in bank accounts, the need for monitoring, surveillance, recordkeeping, data centers, courts and enforcement all but disappears. The system both pays for itself and improves lives. But America is at war with its poor, so “our vast and expensive public service bureaucracy primarily functions to investigate whether individuals’ suffering might be their own fault.”

David Wineberg