Automating inequality : how high-tech tools profile, police, and punish the poor / Virginia Eubanks.
2018
HC79.P6 E89 2018 (Map It)
Available at Cellar
Formats
| Format | |
|---|---|
| BibTeX | |
| MARCXML | |
| TextMARC | |
| MARC | |
| DublinCore | |
| EndNote | |
| NLM | |
| RefWorks | |
| RIS |
Items
Details
Title
Automating inequality : how high-tech tools profile, police, and punish the poor / Virginia Eubanks.
Published
New York, NY : St. Martin's Press, 2018.
Copyright
©2017
Call Number
HC79.P6 E89 2018
Edition
First edition.
ISBN
9781250074317 (hardcover)
1250074312 (hardcover)
9781466885967 (electronic book)
1466885963
9781466885967
1250074312 (hardcover)
9781466885967 (electronic book)
1466885963
9781466885967
Description
260 pages : illustrations ; 22 cm
Other Standard Identifiers
40027901725
99977598098
99977598098
System Control No.
(OCoLC)1013516195
Summary
Eubanks investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. She shows how 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. -- adapted from jacket.
"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. This deeply researched and passionate book could not be more timely."--Publisher's description.
"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. This deeply researched and passionate book could not be more timely."--Publisher's description.
Bibliography, etc. Note
Includes bibliographical references (pages 225-251) and index.
Record Appears in
Portion of Title
How high-tech tools profile, police, and punish the poor
Table of Contents
Introduction: red flags
From poorhouse to database
Automating eligibility in the heartland
High-tech homelessness in the City of Angels
The Allegheny algorithm
The digital poorhouse
Conclusion: dismantling the digital poorhouse.
From poorhouse to database
Automating eligibility in the heartland
High-tech homelessness in the City of Angels
The Allegheny algorithm
The digital poorhouse
Conclusion: dismantling the digital poorhouse.