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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy Hardcover – September 6, 2016
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A 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.
A Boston Globe Best Book of 2016
One of Wired's Required Reading Picks of 2016
One of Fortune's Favorite Books of 2016
A Kirkus Reviews Best Book of 2016
A Chicago Public Library Best Book of 2016
A Nature.com Best Book of 2016
An On Point Best Book of 2016
New York Times Editor's Choice
A Maclean's Bestseller
Winner of the 2016 SLA-NY PrivCo Spotlight Award
“O’Neil’s book offers a frightening look at how algorithms are increasingly regulating people… Her knowledge of the power and risks of mathematical models, coupled with a gift for analogy, makes her one of the most valuable observers of the continuing weaponization of big data… [She] does a masterly job explaining the pervasiveness and risks of the algorithms that regulate our lives.”
—New York Times Book Review
"Weapons of Math Destruction is the Big Data story Silicon Valley proponents won't tell.... [It] pithily exposes flaws in how information is used to assess everything from creditworthiness to policing tactics.... a thought-provoking read for anyone inclined to believe that data doesn't lie.”
“This is a manual for the 21st-century citizen, and it succeeds where other big data accounts have failed—it is accessible, refreshingly critical and feels relevant and urgent.”
"Insightful and disturbing."
—New York Review of Books
“Weapons of Math Destruction is an urgent critique of… the rampant misuse of math in nearly every aspect of our lives.”
“A fascinating and deeply disturbing book.”
—Yuval Noah Harari, author of Sapiens; The Guardian’s Best Books of 2016
“Illuminating… [O’Neil] makes a convincing case that this reliance on algorithms has gone too far.”
“A nuanced reminder that big data is only as good as the people wielding it.”
“If you’ve ever suspected there was something baleful about our deep trust in data, but lacked the mathematical skills to figure out exactly what it was, this is the book for you.”
“O’Neil is an ideal person to write this book. She is an academic mathematician turned Wall Street quant turned data scientist who has been involved in Occupy Wall Street and recently started an algorithmic auditing company. She is one of the strongest voices speaking out for limiting the ways we allow algorithms to influence our lives… While Weapons of Math Destruction is full of hard truths and grim statistics, it is also accessible and even entertaining. O’Neil’s writing is direct and easy to read—I devoured it in an afternoon.”
“Readable and engaging… succinct and cogent… Weapons of Math Destruction is The Jungle of our age… [It] should be required reading for all data scientists and for any organizational decision-maker convinced that a mathematical model can replace human judgment."
—Mark Van Hollebeke, Data and Society: Points
“Indispensable… Despite the technical complexity of its subject, Weapons of Math Destruction lucidly guides readers through these complex modeling systems… O’Neil’s book is an excellent primer on the ethical and moral risks of Big Data and an algorithmically dependent world… For those curious about how Big Data can help them and their businesses, or how it has been reshaping the world around them, Weapons of Math Destruction is an essential starting place.”
“Cathy O’Neil has seen Big Data from the inside, and the picture isn’t pretty. Weapons of Math Destruction opens the curtain on algorithms that exploit people and distort the truth while posing as neutral mathematical tools. This book is wise, fierce, and desperately necessary.”
—Jordan Ellenberg, University of Wisconsin-Madison, author of How Not To Be Wrong
“O’Neil has become [a whistle-blower] for the world of Big Data… [in] her important new book… Her work makes particularly disturbing points about how being on the wrong side of an algorithmic decision can snowball in incredibly destructive ways.”
“O’Neil’s work is so important… [her] book is a vital crash-course in the specialized kind of statistical knowledge we all need to interrogate the systems around us and demand better.”
“Cathy O’Neil, a number theorist turned data scientist, delivers a simple but important message: Statistical models are everywhere, and they exert increasing power over many aspects of our daily lives… Weapons of Math Destruction provides a handy map to a few of the many areas of our lives over which invisible algorithms have gained some control. As the empire of big data continues to expand, Cathy O’Neil’s reminder of the need for vigilance is welcome and necessary.”
“An avowed math nerd, O’Neil has written an engaging description of the effect of crunched data on our lives.”
—Hicklebee’s, San Francisco Chronicle
“By tracking how algorithms shape people's lives at every stage, O'Neil makes a compelling case that our bot overlords are using data to discriminate unfairly and foreclose democratic choices. If you work with data, or just produce reams of it online, this is a must-read.”
“Lucid, alarming, and valuable… [O’Neil’s] writing is crisp and precise as she aims her arguments to a lay audience. This makes for a remarkably page-turning read for a book about algorithms. Weapons of Math Destruction should be required reading for anybody whose life will be affected by Big Data, which is to say: required reading for everyone. It’s a wake-up call – a journalistic heir to The Jungle and Silent Spring. Like those books, it should change the course of American society.”
"[O'Neil's] propulsive study reveals many models that are currently 'micromanaging' the US economy as opaque and riddled with bias."
“You don’t need to be a nerd to appreciate the significance of [O’Neil’s] message… Weapons is a must-read for anyone who is working to combat economic and racial discrimination.”
"Cathy O’Neil’s book... is important and covers issues everyone should care about. Bonus points: it’s accessible, compelling, and—something I wasn’t expecting—really fun to read.”
—Inside Higher Ed
“Often we don’t even know where to look for those important algorithms, because by definition the most dangerous ones are also the most secretive. That’s why the catalogue of case studies in O’Neil’s book are so important; she’s telling us where to look.”
“O’Neil is passionate about exposing the harmful effects of Big Data–driven mathematical models (what she calls WMDs), and she’s uniquely qualified for the task… [She] makes a convincing case that many mathematical models today are engineered to benefit the powerful at the expense of the powerless… [and] has written an entertaining and timely book that gives readers the tools to cut through the ideological fog obscuring the dangers of the Big Data revolution.”
—In These Times
“In this simultaneously illuminating and disturbing account, [O’Neil] describes the many ways in which widely used mathematic models—based on ‘prejudice, misunderstanding, and bias’—tend to punish the poor and reward the rich… 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.”
—Kirkus Reviews (starred)
“Even as a professional mathematician, I had no idea how insidious Big Data could be until I read Weapons of Math Destruction. Though terrifying, it’s a surprisingly fun read: O’Neil’s vision of a world run by algorithms is laced with dark humor and exasperation—like a modern-day Dr. Strangelove or Catch-22. It is eye-opening, disturbing, and deeply important.”
—Steven Strogatz, Cornell University, author of The Joy of x
“This taut and accessible volume, the stuff of technophobes’ nightmares, explores the myriad ways in which largescale data modeling has made the world a less just and equal place. O’Neil speaks from a place of authority on the subject… Unlike some other recent books on 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… eerily prescient.”
"Well-written, entertaining and very valuable."
—Times Higher Education
"Not math heavy, but written in an exceedingly accessible, almost literary style; [O'Neil's] fascinating case studies of WMDs fit neatly into the genre of dystopian literature. There's a little Philip K. Dick, a little Orwell, a little Kafka in her portrait of powerful bureaucracies ceding control of the most intimate decisions of our lives to hyper-empowered computer models riddled with all of our unresolved, atavistic human biases."
“Through harrowing real-world examples and lively story-telling, Weapons of Math Destruction shines invaluable light on the invisible algorithms and complex mathematical models used by government and big business to undermine equality and increase private power. Combating secrecy with clarity and confusion with understanding, this book can help us change course before it’s too late.”
—Astra Taylor, author of The People’s Platform: Taking Back Power and Culture in the Digital Age
"Weapons of Math Destruction is a fantastic, plainspoken call to arms. It acknowledges that models aren't going away: As a tool for identifying people in difficulty, they are amazing. But as a tool for punishing and disenfranchising, they're a nightmare.”
—Cory Doctorow, author of Little Brother and co-editor of Boing Boing
“Many algorithms are slaves to the inequalities of power and prejudice. If you don’t want these algorithms to become your masters, read Weapons of Math Destruction by Cathy O’Neil to deconstruct the latest growing tyranny of an arrogant establishment.”
—Ralph Nader, author of Unsafe at Any Speed
“In this fascinating account, Cathy O'Neil leverages her expertise in mathematics and her passion for social justice to poke holes in the triumphant narrative of Big Data. She makes a compelling case that math is being used to squeeze marginalized segments of society and magnify inequities. Her analysis is superb, her writing is enticing, and her findings are unsettling.”
—danah boyd, founder of Data & Society and author of It’s Complicated
"From getting a job to finding a spouse, predictive algorithms are silently shaping and controlling our destinies. Cathy O'Neil takes us on a journey of outrage and wonder, with prose that makes you feel like it's just a conversation. But it’s an important one. We need to reckon with technology.”
—Linda Tirado, author ofHand to Mouth: Living in Bootstrap America
“Next time you hear someone gushing uncritically about the wonders of Big Data, show them Weapons of Math Destruction. It’ll be salutary.”
—Felix Salmon, Fusion
About the Author
- Publisher : Crown; 1st edition (September 6, 2016)
- Language : English
- Hardcover : 272 pages
- ISBN-10 : 0553418815
- ISBN-13 : 978-0553418811
- Item Weight : 12.8 ounces
- Dimensions : 5.79 x 1.09 x 8.54 inches
- Best Sellers Rank: #249,122 in Books (See Top 100 in Books)
- Customer Reviews:
About the author
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Top reviews from the United States
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Unfortunately the logic in the book is a dumpster fire. I was astonished given that the author holds a PhD in mathematics... a very logical discipline.
The main thesis of the book is that there are certain conditions for an algorithm in which it can become a 'weapon of math destruction', and tries to show examples of these cases. O'Neil is decidedly anti-big data and anti-modeling in this book.
Here are my main complaints:
1. Her treatment of all of the examples is offensive to the experts who actually do social science in those fields. She clearly has only a surface knowledge of these issues, makes many factual errors, and does not actually know what current social scientists are working on. For example, in the section about policing, O'Neil says that if the Chicago Police Department hired her as their data scientist (!) she could make these biases and issues with the models go away, all while completely oblivious to what current economists, sociologists, and other experts are working on.
2. The claims made by O'Neil in this book are all testable hypotheses, however she makes NO effort to use data to make her argument, and instead relies on scant anecdotes and sweeping generalizations.
3. O'Neil was contradictory as to whether people are the problem or algorithms are the problem. For example, in the section about Starbucks and employee scheduling software she slammed the managers who took control over the algorithm, but then later explained that we don't have enough people actually being involved who adjust the algorithms as necessary... So which is it?
4. She misses the nuance between 'good' and 'bad' aspects of models. For example, when discussing the US News rating system for colleges, she argues that it isn't appropriate to rank schools. Then she goes on to attack for-profit colleges, while failing to acknowledge that the US News rating system can help guide someone who is underprivileged and doesn't have college counselors to tell them that the for-profit colleges are terribly terribly ranked.
5. She needs to look up the word 'arbitrary' in the dictionary. I'll quote the definition here: "based on random choice or personal whim, rather than any reason or system". Many times throughout the book she describes the choices of models in her examples as 'arbitrary'. A model is the exact OPPOSITE of arbitrary. It makes choices based on the defined rules of the program...
6. There is no original content or analysis in this book, beyond her coining of the phrase of 'weapons of math destruction'.
7. I'm confused why people say the book is well written. It isn't. It rambles and often strays away from the thesis.
In short, she does a disservice to the nuance involved with data and algorithms. She identifies some of the important issues near the beginning (e.g. sample size, out-of-sample conclusions, poor objective functions), however, her poor understanding of her examples, and hack-job of an argument is unfortunate and ultimately damning.
As a research scientist in the field of analytics I support most all her research recommendations. The technology implementing analytic models (e.g. predictive analytics and AI) is often leaving the supporting science behind. Mastering the science behind, rather than just advancing, these analytic technologies is as important as it is currently unpopular for research investment. But, if these inquiries into “WMD” are to be defensible research with persuasive results they cannot be colored by social and logical biases like Ms. O’Neil’s personal definition of morality or what a utopian society would look like.
Cathy O’Neil has a PhD in math from Harvard, taught at Barnard, decided to make three times the money by working as a “quant” on Wall Street, specifically for the hedge fund D. E. Shaw. Of the numerous wry observations she makes in the book, she compares working at D.E. Shaw to the structure of Al Qaeda. Information was tightly controlled in individual “cells.” No one (probably even the big boys) understood the entire structure which prevented someone “walking” to a rival. The financial meltdown of 2008, when suddenly the quants, and others, realized that a strawberry picker named Alberto Ramirez, making $14,000 a year, really couldn’t afford the $720,000 he financed in Rancho Grande, CA,, and therefore the “Triple A” rating on the bonds issued based on the mortgage was phony, proved to be her “Saul on the road to Damascus moment,” which eventually led to this book. (She doesn’t make the point that the damage done by the quants, in terms of lost homes and jobs, to so many Americans, was far, far greater than Al Qaeda’s wildest aspirations.)
In her book, O’Neil goes far beyond Wall Street to other segments of our society: colleges, the judicial system, insurance, advertising, employment, teacher evaluations, credit scores, and political campaigns and Facebook.
Consider colleges. It was US News and World Report that dreamed up the idea of ranking colleges based on “objective” quantitative criteria. They convinced others to play along, in particular the colleges themselves. And so, from the perspective of a university President, “…they were at the summit of their careers dedicating enormous energy toward boosting performance in fifteen areas defined by a group of journalists at a second-tier news magazine.” A most important area was totally omitted: “value for money,” a standard criteria for most Amazon Vine reviews. And so, as she says, to meet these journalists’ criteria, the cost of higher education rose 500% between 1985 and 2013. She cites a couple of examples how colleges “gamed” the system. The most interesting was King Abdulaziz University in Saudi Arabia. Its math department had been around TWO years, in 2014, when it came in 7th place in the world, behind Harvard, but ahead of MIT and Cambridge! How? It searched the professional journals for professors with the most citations, one of the criteria in the algorithm, offered the professors $72,000 a year for three weeks of work as “adjunct faculty.” Voila.
In public school teacher evaluations in the USA, O’Neil cites the example of a well-respected teacher who was fired for being in the bottom 10% in teacher evaluations. How? Apparently the teachers from the PREVIOUS year had falsified the students’ standardized testing results. The following year, when the well-respected teacher did not, it appeared to the algorithm that the students had declined. No appeal or common sense. She was fired.
Insurance is a personal bugaboo with me. O’Neil confirmed what I learned the hard way. A MAJOR factor in determining the price of insurance is an algorithm that determines which customers are unlikely to switch insurance companies – and those customers are charged the most! When I finally figured this out, the hard way, a few years back, the company that famously proclaims that you can “save 15% or more” was actually willing to drop my insurance premium 30% because I was changing, which I still did, to another company that offered the same coverage for 50% less. (I’ll be changing from that company in a couple of years, of course.) (What a racket.)
Another fascinating section is on how our on-line behavior is monitored, which changes not only the ads we see, but the very news. And how much effort is expended in political campaigns on those few undecided voters in Florida and Ohio. Wow. Truly calls for the abolition of the Electoral College.
Finally, my own example. I once worked for the COO of the most famous hospital in the aforementioned Saudi Arabia. He called me in one day and asked if I could do standard deviations. Thanks to Bill Gates, et al., I assured him I could readily do them. “Then please do them on all the doctors’ salaries, per department”. Again, thanks to Bill, it was done in a day. Why, oh why? It was the COO’s own “algorithm.” When he met monthly with each department Chair, to discuss physician evaluations and salary increases, there would be nothing “personal” involved. He could point to this objective report, and express his concerns about the “standard deviation” of the salaries within the department. And depending on – hum – the circumstances, he could say: I think the standard deviation is “too high” (or, of course, “too low”). The “basis” for giving out a 2 ½% or 5% salary increase. “Clever.”
As for O’Neil’s book, 5-stars, plus.
Top reviews from other countries
If you are looking for a really in depth text, this is not it. This is meant for everyone and in that respect it is a good book. When I started reading it I thought perhaps it could do with the Michael Lewis touch (Flashboys, Moneyball etc) but when I finished I thought not. It looks like this is the way the future looks, and it is not pretty the way it is right now. Let's hope that the technology and scale leads to greater beneifts to all, and not mass categorisation with a dumb central machine.
The author passion for the subject can be felt through the book and although enjoyed it did leave me feeling a little saddened to see so many examples of poorly implemented analytics.
The book would have benefitted from a broader perspective and also included success stories to show how data can also be a force for good to simplify and improve our lives. At the end of the day these are tools and it’s how people use them that can produce these WMD’s.
Also reminds us of the need to educate the wider community on how data is used and that data asset needs to benefit everyone.
It's tough luck being the 1 but it just means you will have to fight harder. It gives people the excuse to blame it on 'generalisation' and allows individuals to scream 'I am unique, you must take under account me as well!!', which in my honest opinion shows a very massive degree of selfishness and narcissism. People are amazing because we adapt and find identity in this adaptation but also respect.
Book is well written though and does have examples. It just doesn't evoke positivity in me.