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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

3.88  ·  Rating details ·  22,500 ratings  ·  2,882 reviews
We live in the age of the algorithm. Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.
But as mathematician and data scientist Cathy O
Hardcover, 259 pages
Published September 6th 2016 by Crown
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Andrew Walls The author explores the ethical and moral dilemmas generated by algorithms that contain within themselves the prejudices, biases and preconceptions of…moreThe author explores the ethical and moral dilemmas generated by algorithms that contain within themselves the prejudices, biases and preconceptions of the algorithm designers. At times, designers are not conscious of their reliance on biased data and design, at other times, they are. This is a fascinating book and particularly relevant as all of us are pulled into a data-driven world.(less)
Zach It's a primer on the development and consequences of using algorithms to make complex decisions. I don't think the author would necessarily disagree w…moreIt's a primer on the development and consequences of using algorithms to make complex decisions. I don't think the author would necessarily disagree with the data analysis or conclusions as it applies to the observed data. I think she would, however, question the validity of relying on those conclusions as the primary decision making criterion. Succinctly, solid data analysis with sensible conclusions can become a WMD when turned into a predictive algorithm. WMDs can be innocently wrong (eg someone who is a low-risk borrower might have a low credit score because they were sent to collections for a parking ticket they didn't know they had because they moved cross-country... not that I'm bitter), WMDs can be gamed (eg the collateralized debt obligations that crashed the economy in 2008 are largely due to bundling higher-risk loans in a way that the algorithms thought they were lower-risk), and WMDs can have consequences that most of us don't like (eg social media feed algorithms sensibly conclude from the data that people engage longer with content that induces negative emotions, which makes them $$ but makes us unhappy).(less)

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Dec 20, 2016 rated it did not like it
Shelves: owned, dfa-book-club
This was such a Malcolm Gladwell take on data science. I think this book touches on an important subject, and people should be aware of the issues O'Neil discusses. But instead of doing a deep dive into the subject, it just felt like a list of bad algorithms with instances of the people they hurt. It didn't contain many examples of "WMDs" that I had not already heard of, and that might be because she cited the New York Times for *like* all her case studies.

As someone who works in the field, I do
Oct 22, 2017 rated it really liked it
Shelves: favorites
I'm a data person. I pride myself on being logical and looking at the numbers before making decisions. And for quite a few years, I worked at a data visualization company and was a self-professed data geek. But can more data actually lead to worse results? That is what Weapons of Math Destruction tries to understand.

Insightful and timely, this book provides a detailed look at how algorithms based on big data don't always tell the truth or lead to a more fair world as they are purported to do. Ra
O’Neil deserves some credit right off the bat for not waiting until her retirement from the hedge fund where she worked to tell us the secrets of how corporations use big data (our data). Underlying the collection and use of big data is an attempt to utilize efficiencies in the market place for goods, money, and talent. Big data ostensibly can also “set us free” from time constraints and uneven knowledge dispersal. Conversely the opposite is often true. We are at the mercy of how our own data is ...more
Leo Walsh
Dec 22, 2016 rated it it was amazing
Captivating. Insightful. And important. A 50,000 foot view of how automated big-data is a great tool for understanding human nature. How it has great promise to make our lives easy. And yet, a very real takedown of how systems engineers -- and corrupt power-seekers, like corporate executives and for-profit universities -- misuse this powerful tool. And the even worse cases where people start with good intentions, like ridding school systems of bad teachers, only to toss out "false negatives."

I f
Clif Hostetler
Oct 14, 2016 rated it it was amazing  ·  review of another edition
Shelves: current-events
"Welcome to the dark side of big data." Thus the author concludes the Introduction section of this book. Computers and the internet have enabled us to advance into the new world of algorithms and big data with ramifications that most people are unaware of.

Surfing the web, clicking "like" in Facebook, Googling (i.e.searching on line), and making online purchases are common examples where big data is either tracking and potentially impacting our lives. Some of these are benign and can be helpful.
Mario the lone bookwolf (is on a longer vacation)
Is it legitimate to reduce people to the data that can be extracted from them?

Please note that I put the original German text at the end of this review. Just if you might be interested.

Especially the predictions made possible by big data are a frightening aspect so that behavior and personal development can be predicted with increasing probability. Also, like any artificial intelligence, the algorithms and programs become more and more efficient, both in parallel with the growing amount of data
Aug 26, 2018 rated it it was amazing
We like to think of mathematics as basically pure and free from the nastier side-effects of human nature. And this purity rubs off – so that the closer a science is to being able to be described in numbers, the more highly we regard it – so, physic is seen as somehow higher than biology, and economics than anthropology. That is, if you can predict behaviour on the basis of an algorithm – whether that be the behaviour of a billiard ball or a homeless person – then this is proper science and it ha ...more
Aug 22, 2016 rated it really liked it
Shelves: netgalley, nonfiction
This book did a nice job describing large-scale data modeling and its pitfalls in a very accessible manner. It is so easy to think of computer algorithms as unbiased; however, the author demonstrates how they really do discriminate. Next time I teach a class involving statistics, I may use this book to show students how it is dangerous to blindly believe the numbers.
Nov 27, 2016 rated it it was ok
Shelves: good-non-fiction
For the most part, WMD is a rant with only impractical statements as solutions.

The author is onto something critically important when one reads the title of the book and goes through the first few pages. However, it is a tragedy to see the author falling in love with her own phrase WMD and completely losing the plot. The examples used are good in the beginning but soon turn ridiculous (they would be laughable if not so lamentable for the people involved). In the process, the author loses her cr
David Rubenstein
Dec 10, 2017 rated it really liked it
Shelves: politics, mathematics
The subtitle of this book, How Big Data Increases Inequality and Threatens Democracy really says it all. Big data has come into our lives in numerous ways, and many of them are a scourge on our lives. Big data, in and of itself, is not to blame, but the uses to which it is put are often outrageous. Take the case of automated teacher evaluations. These are often based on the improvement of students' scores. It seems like a no-brainer, and since the scores take into account the improvement rather ...more
Jan 24, 2017 rated it liked it  ·  review of another edition
Shelves: politics, science
Big Data is opaque, complicated, managed by profit-seeking corporations, and is more and more dictating certain societal conditions: from getting a job to applying to college to receiving healthcare. "Data," on its own, seems amoral, a way to implement systems that are more fair. But O'Neil's point in this book is that all algorithms include basic assumptions, and sometimes those basic assumptions are full of bias and not grounded in fact. If the algorithms aren't regularly inspected, they creat ...more
Oct 25, 2016 rated it liked it  ·  review of another edition
Book reviews are all about expectations, and honestly I, as someone doing data science and grappling with issues, expected more. With a data scientist writing a full length book inditing data science one expects a deep dive revealing real points. Instead it ends up being a very surface level essay without the deeper exploration and meaning one expects from a full length work. Perhaps more worrisomely, her own definition of a WMD it introduces is often worked around to bring in arguments she want ...more
Maru Kun
Aug 17, 2017 rated it really liked it
Forget those cute pastel illustrations from the fifties with their flying cars, robot servants and dreams of unlimited leisure. Our future has finally arrived and for most of us, especially for the less rich and less privileged who won’t qualify for individualized attention, the computer says “No”.

‘Weapons of Math Destruction’ is a timely book about the increasing influence of algorithms to control the news we see, the jobs we can get and the politicians we vote for; algorithms working tirelessl
Chad Kohalyk
Solid overview of the various mathematical models that govern our education, labour, wealth, and commerce. O'Neil packs in many examples and unpacks how simplistic, unfair and damaging to already disadvantaged people these models can be. As someone who worked on the front lines of developing models for predictive internet shopping, I was familiar with many of the tactics mentioned in this book, and their ethical shortcomings (which finally led to me leaving the business). What she says is entire ...more
Jack Teng
Oct 07, 2016 rated it it was amazing
I can't stress how important of a book this is. I don't think people really know how the obsession with Big Data and algorithms is about to control/influence our lives. I suppose I sound paranoid, but I really don't think I am. There are too many tinkerers out there who have some degree of competence at math and who think they'll solve all the world's problems with the next greatest optimization formula, and yet they lack even the most basic experience in asking proper research questions and und ...more
C.P. Cabaniss
Jan 28, 2017 rated it it was ok
Shelves: nonfiction, reviewed
*I received a copy of this book through Netgalley. All thoughts are my own.*

This book did not turn out to be what I was expecting. I expected O'Neil to go more in depth about the math behind data she was discussing, to explore the algorithms in greater detail. That was not what I got, however. This book turned out to be more of a superficial look at some of the ways big data can/has impacted society in the author's opinion. And while I found some of the material presented interesting and informa
Oct 12, 2017 rated it it was ok  ·  review of another edition
It's good to critique what the author calls WMDs, but for me this book missed the mark.

For example, the entire example of teacher-rating in DC is a red herring. The real question is: What is proven to deliver success in an urban US school system? (Answer: Hope and Despair in the American City: Why There Are No Bad Schools in Raleigh) So it's valid to point out the silliness of a silly GIGO teacher-rating algorithm, but it's a distraction to fall down the vortex of dissecting that silliness in d
Margaret Sankey
Sep 16, 2016 rated it it was amazing
I was really delighted to see this book on the list of nominations for the National Book Award--O'Neil was a math professor, then hedge fund analyst, then Occupy activist, now excellent non-fiction explicator of the power that we've given algorithms in daily life. Certainly, the old way, in which a human bank manager or college admissions officer selected people for loans or Harvard reflected significant prejudices--but have we gone too far in the other direction, thinking that hard data will er ...more
Graeme Roberts
Apr 23, 2017 rated it it was ok

Cathy O'Neil writes well and provides some good information, but I found the fundamental thesis of Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy to be foolish and irresponsible. The title, condensed inevitably to WMD, is used promiscuously to describe any application of data science, statistics, or even information technology that she considers to be unfair or discriminatory. In some cases, she may be right; some applications are used by the greedy and

Jan 20, 2018 rated it liked it
A short and concise overview of the problems being wrought by the algorithms that are now quietly governing our society. While the overview is useful, I was a bit surprised at how little new information that there was in here. The issues that she raises should be familiar to anyone who has been following the impact of Big Data in even a cursory way. Facebook news bubbles, insurance profiles and other common phenomena are the main examples she uses. I did appreciate the social justice focus of th ...more
Nick Klagge
Feb 04, 2017 rated it really liked it
Cathy O'Neil was my professor for number theory in college, I think in 2006. I thought she was a great teacher, but didn't keep in touch at all after the class. I was somewhat aware that she was involved with Occupy Wall Street's financial policy arm, and after I heard about this book, also learned that she had been co-hosting a podcast on Slate (which she is now about to leave!--but I still have a lot of back-episodes to listen to).

I'm broadly in agreement with the thrust of her argument in thi
Sep 04, 2016 rated it really liked it
This book shows the hidden ways in which the use of "Big Data" is much more far-reaching and harmful than expected. Big data refers to the massive amount of information now available because of computers that is collected and analyzed and sold to third parties.

In particular, as the author demonstrates convincingly, applications of Big Data “punish the poor and the oppressed in our society, while making the rich richer.” She paints a sobering picture.

The author calls the mathematical models emplo
Kurt Pankau
Sep 20, 2016 rated it it was amazing
My father, in one of his grouchier get-off-my-lawn moments, complained to me about computers in the workplace. Specifically, it bothered him that people were so trusting in the software that they were unwilling to gut-check outputs. This conversation happened maybe twenty years ago, but it stuck with me, and part of the reason is because he was absolutely right. We've all heard the phrase "garbage in, garbage out" to describe this phenomenon.

O'Neil takes the idea of "garbage in, garbage out" and
Tanja Berg
Feb 25, 2018 rated it really liked it  ·  review of another edition
Shelves: science, non-fiction
Much of our lives are now influenced by algorithms. These are deemed to be neutral, but in fact many are based on models that are glaringly discriminatory. Zip codes stand in for race, for example. The poor are being particularly targeted for pay-day loans. Teacher are measured on opaque proxies that do no reflect their skills at all. Your credit score is as much a result of the group of people you are thrown in with, as with your own behavior. These algorithms are what the author calls "weapons ...more
Sep 22, 2016 rated it liked it
We've all seen the Big Data books: the future is now! A/B testing forever! AlphaGo crushed it! OkCupid says you shouldn't have a shirtless fish pic, you adorably dull redneck!

But Big Data has a darkside, and O'Neil goes through each segment of our life to show how these "models" can be used against us, to extract goods from us, and to keep us poor. Unfortunately, she also loses her argumentative power that could come with nuance, and she has to disregard nuance in order to make it understandable
Sep 29, 2016 rated it really liked it
Shelves: nonfiction
"Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that's something only humans can provide."

So, for work, I read a lot about big data. A lot. And it's all basically *jackoff motion* uhhnnnggg big dataaaa unnnnnnngggghhh yeah. And that makes me want to die.

This book is refreshingly critical of big data and algorithms, from a blessedly human approach. You might expect a lot of statistics and dryness, but it's a lot of real life stories
Roxana Chirilă
Jan 23, 2018 rated it really liked it  ·  review of another edition
Good stuff. Scary stuff. A book about how badly created algorithms are screwing people over in all sorts of ways, all for the sake of "simplifying" processes - also a book about part of what's wrong with the US, because it isn't always obvious when you're living in Europe and noticing that people there are acting crazy about their credit scores and zip codes.

I have some issues with her interpretation of things (like crying out "racism" all over the place, and making contradictory points which am
Wick Welker
Dec 09, 2020 rated it it was amazing
Shelves: nonfiction
Big data codifies prejudice and penalizes the poor.

A decent take on the "garbage in-garbage out" theory of data utilization. Cathy O'Neil appears aptly qualified to comment on the phenomenon of data models becoming an amplified version of societies biggest problems. O'Neil has invented her own term, Weapons of Math Destruction (WMDs) to lift the veil on a hidden but very active phenomenon that is perpetrating the racial and class biases that are already prevalent.

Per O'Neil, WMDs are any data a
This is not a math book, it's a book about how math is used and misused. Anyone interested in public policy, management theories, or scoring systems should read this.

Math is wonderful but it only does what you tell it to. The thesis of this book is that algorithms used in many facets of our lives can be poorly designed, measure the wrong things, or are just plain misapplied. Just because a computer spit out a number or some fancy looking statistics doesn't mean it's fair or should be blindly tr
Lubinka Dimitrova
I'm rather sorry that I only got around to reading this book in December, otherwise I would have voted for it on Goodreads Choice Awards. A concise, clear-written and eye-opening book, it is even more frightful, for the fact that is it in fact science fiction of the harrowing kind becoming reality as we speak. I belong to the lucky (?) part of the world where technology is still lagging behind what's the norm now in America, but sadly it's unavoidable that sooner or later we'll all catch up with ...more
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Cathy O’Neil is the author of the bestselling Weapons of Math Destruction, which won the Euler Book Prize and was longlisted for the National Book Award. She received her PhD in mathematics from Harvard and has worked in finance, tech, and academia. She launched the Lede Program for data journalism at Columbia University and recently founded ORCAA, an algorithmic auditing company. O’Neil is a regu ...more

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41 likes · 6 comments
“Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that’s something only humans can provide. We have to explicitly embed better values into our algorithms, creating Big Data models that follow our ethical lead. Sometimes that will mean putting fairness ahead of profit.” 34 likes
“Here we see that models, despite their reputation for impartiality, reflect goals and ideology. When I removed the possibility of eating Pop-Tarts at every meal, I was imposing my ideology on the meals model. It’s something we do without a second thought. Our own values and desires influence our choices, from the data we choose to collect to the questions we ask. Models are opinions embedded in mathematics.” 14 likes
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