Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
(Libby/OverDrive eAudiobook)

Book Cover
Average Rating
Contributors
O'Neil, Cathy Author, Narrator
Published
Books on Tape , 2016.
Status
Available from Libby/OverDrive

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Description

Longlisted for the National Book Award | New York Times BestsellerA former Wall Street quant sounds an alarm on the mathematical models that pervade modern life and threaten to rip apart our social fabric.We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated.But as Cathy O’Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his zip code), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.” Welcome to the dark side of Big Data.Tracing the arc of a person’s life, O’Neil exposes the black box models that shape our future, both as individuals and as a society. These “weapons of math destruction” score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health.O’Neil calls on modelers to take more responsibility for their algorithms and on policy makers to regulate their use. But in the end, it’s up to us to become more savvy about the models that govern our lives. This important book empowers us to ask the tough questions, uncover the truth, and demand change.

More Details

Format
eAudiobook
Edition
Unabridged
Street Date
09/06/2016
Language
English
ISBN
9780735286528

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Published Reviews

Publisher's Weekly Review

This taut and accessible volume, the stuff of technophobes' nightmares, explores the myriad ways in which large-scale data modeling has made the world a less just and equal place. O'Neil speaks from a place of authority on the subject: a Barnard professor turned Wall Street quant, she renounced the latter profession after the 2008 market collapse and decided to educate laypeople. Unlike some other recent books about data collection, hers is not hysterical; she offers more of a chilly wake-up call as she walks readers through the ways the "big data" industry has facilitated social ills such as skyrocketing college tuitions, policing based on racial profiling, and high unemployment rates in vulnerable communities. She also homes in on the ways these systems are frequently destructive even to the privileged: sloppy data-gathering companies misidentify people and flag them as criminals, and algorithms determine employee value during company-wide firings. The final chapter, in which O'Neil discusses Facebook's increasing electoral influence, feels eerily prescient. She offers no one easy solution, but has several reasonable suggestions as to how the future can be made more equitable and transparent for all. Agent: Jay Mandel, William Morris Endeavor. (Sept.) © Copyright PWxyz, LLC. All rights reserved.

(c) Copyright PWxyz, LLC. All rights reserved
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Library Journal Review

As mathematical models affect more and more aspects of our lives, it is crucial to understand that algorithms are not neutral, free from human prejudice and fallibility; instead, those biases and failings are encoded into the systems. Data scientist O'Neil, who blogs at mathbabe.org, explores this premise in depth and chillingly describes the extent to which data-driven, algorithm-based decision making in such areas as hiring, policing, lending, education, and health care actually increases inequality. With barely contained exasperation, O'Neil chronicles the way these "weapons of math destruction"-opaque and unregulated-shape all lives, and, especially, those of the poor. More than just sounding the clarion call to action, O'Neil seeks to empower her readers to ask questions about the algorithms and to demand change. Though the subject matter is alarming and dire, O'Neil's dry wit and ease when describing complicated ideas is more enlivening than depressing. VERDICT This important book will be eye-opening to many readers, possibly even those involved with the kind of models O'Neil criticizes.-Rachel Bridgewater, Portland Community Coll. Lib., OR © Copyright 2016. Library Journals LLC, a wholly owned subsidiary of Media Source, Inc. No redistribution permitted.

(c) Copyright Library Journals LLC, a wholly owned subsidiary of Media Source, Inc. No redistribution permitted.
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Kirkus Book Review

How ill-conceived algorithms now micromanage Americas economy, from advertising to prisons.Welcome to the dark side of Big Data, writes math guru ONeil (Doing Data Science: Straight Talk from the Frontline, 2013, etc.), a blogger (mathbabe.org) and former quantitative analyst at the hedge fund D.E. Shaw. In this simultaneously illuminating and disturbing account, she describes the many ways in which widely used mathematic modelsbased on prejudice, misunderstanding, and biastend to punish the poor and reward the rich. The most harmful such models, which she calls Weapons of Math Destruction, often have devastating effects on people when they are going to college, borrowing money, getting sentenced to prison, or finding and holding a job. For example: credit scores are used to evaluate potential hires (assuming bad scores correlate with bad job performance, which is often not true); for-profit colleges use data to target and prey on vulnerable strivers, often plunging them into debt; auto insurance companies judge applicants by their consumer patterns rather than their driving records; crime predictive software often leads police to focus on nuisance crimes in impoverished neighborhoods. As the author notes, the harmful effects are apparent when a poor minority teenager gets stopped, roughed up, and put on warning by the local police, or when a gas station attendant who lives in a poor zip code gets hit with a higher insurance bill. She notes the same mathematical models place the comfortable classes of society in their own marketing silos, jetting them off to vacations in Aruba, wait-listing them at Wharton, and generally making their lives smarter and easier. The author writes with passiona few years ago she became disillusioned over her hedge fund modeling and joined the Occupy movementbut with the authority of a former Barnard professor who is outraged at the increasingly wrongheaded use of mathematics. She convincingly argues for both more responsible modeling and federal regulation. An unusually lucid and readable look at the daunting algorithms that govern so many aspects of our lives. Copyright Kirkus Reviews, used with permission.

Copyright (c) Kirkus Reviews, used with permission.
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Library Journal Reviews

As mathematical models affect more and more aspects of our lives, it is crucial to understand that algorithms are not neutral, free from human prejudice and fallibility; instead, those biases and failings are encoded into the systems. Data scientist O'Neil, who blogs at mathbabe.org, explores this premise in depth and chillingly describes the extent to which data-driven, algorithm-based decision making in such areas as hiring, policing, lending, education, and health care actually increases inequality. With barely contained exasperation, O'Neil chronicles the way these "weapons of math destruction"—opaque and unregulated—shape all lives, and, especially, those of the poor. More than just sounding the clarion call to action, O'Neil seeks to empower her readers to ask questions about the algorithms and to demand change. Though the subject matter is alarming and dire, O'Neil's dry wit and ease when describing complicated ideas is more enlivening than depressing. VERDICT This important book will be eye-opening to many readers, possibly even those involved with the kind of models O'Neil criticizes.—Rachel Bridgewater, Portland Community Coll. Lib., OR. Copyright 2016 Library Journal.

Copyright 2016 Library Journal.
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Publishers Weekly Reviews

This taut and accessible volume, the stuff of technophobes' nightmares, explores the myriad ways in which large-scale data modeling has made the world a less just and equal place. O'Neil speaks from a place of authority on the subject: a Barnard professor turned Wall Street quant, she renounced the latter profession after the 2008 market collapse and decided to educate laypeople. Unlike some other recent books about data collection, hers is not hysterical; she offers more of a chilly wake-up call as she walks readers through the ways the "big data" industry has facilitated social ills such as skyrocketing college tuitions, policing based on racial profiling, and high unemployment rates in vulnerable communities. She also homes in on the ways these systems are frequently destructive even to the privileged: sloppy data-gathering companies misidentify people and flag them as criminals, and algorithms determine employee value during company-wide firings. The final chapter, in which O'Neil discusses Facebook's increasing electoral influence, feels eerily prescient. She offers no one easy solution, but has several reasonable suggestions as to how the future can be made more equitable and transparent for all. Agent: Jay Mandel, William Morris Endeavor. (Sept.)

[Page ]. Copyright 2016 PWxyz LLC

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Citations

APA Citation, 7th Edition (style guide)

O'Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (Unabridged). Books on Tape.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

O'Neil, Cathy. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Books on Tape.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy Books on Tape, 2016.

Harvard Citation (style guide)

O'Neil, C. (2016). Weapons of math destruction: how big data increases inequality and threatens democracy. Unabridged Books on Tape.

MLA Citation, 9th Edition (style guide)

O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy Unabridged, Books on Tape, 2016.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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