• Weapons of Math Destruction

  • How Big Data Increases Inequality and Threatens Democracy
  • Written by: Cathy O'Neil
  • Narrated by: Cathy O'Neil
  • Length: 6 hrs and 23 mins
  • Unabridged Audiobook
  • Release date: 2016-09-06
  • Language: English
  • Publisher: Random House Audio
  • 4.5 out of 5 stars (39 ratings)

Price: CDN$ 37.05

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Audible Editor Reviews

"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." (Steven Strogatz, Cornell University, author of The Joy of x)

Publisher's Summary

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 troublingly, 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 paroles, 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 savvier about the models that govern our lives. This important book empowers us to ask the tough questions, uncover the truth, and demand change.

©2016 Cathy O'Neil (P)2016 Random House Audio

What the critics say

" 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 )
" Weapons of Math Destruction shines invaluable light on the invisible algorithms and complex mathematical models used by government and big business." (Astra Taylor, author of The People's Platform)

What members say

Average Customer Ratings

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Amazing Listen!

I really enjoyed the storyline working its way up through society showing exactly how WMD’s really affect these areas. The narrator was impeccable.

Overall a recommended must read for the techies and the curious.

1 of 1 people found this review helpful

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  • Jay
  • 2019-03-12

Excellent Audiobook

Very interesting and pertinent topic. The author provides a lot of insight into the adverse impacts of the darker side of data science.

The examples cited are very very diverse and relevant to the discussion. What makes this particular book so effective is the author's ability to abstract the mathematical details and provide very accessible explanations of how the math has impacted society in certain areas.

My only critique is that while using the term WMD is catchy, I think it is a bit overused in the book and the author should just stick to using terms like model, algorithm, etc.

Highly recommended.

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Lefty/communist propaganda...

Couldn't get past chapter 2. Identidity politics at its best.

I wish I could ask for a refund.

0 of 1 people found this review helpful

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  • Stephen
  • 2016-10-02

A fascinating and startling look at where big data is blind

This book is totally worth the listen for the intro and first chapter alone. It's very well-written and easy to follow, and manages to tell clear stories about how the software we use to assess teacher performance or insurance risk is all to often encoded with the prejudices and blind spots of the people who make it. It shows how that is already damaging equality and democracy, and warns of areas where it may get worse.

As a software designer, the one thing I would have loved from this book would be a little more depth about how software products might avoid these pitfalls. However, I'm probably coming at this book with unfair expectations, and it's likely a subject I just need to research more deeply.

Overall, if you enjoy podcasts like Freakonomics and Planet Money, you'll probably love this. Happy I listened!

11 of 11 people found this review helpful

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  • Laurent Bourgault-Roy
  • 2017-01-08

More are US social problems that WMD

A WMD, or weapon of math destruction, are usage of algorithm that end up being discriminatory toward some people, or that cause problem with their wide scale deployment. For example, an algorithm that identify poor people can deny them services that help them, making them poorer. The algorithm prediction become self-fulfilling and prevent people from improving their condition.  

The premise of the book is very good, and there are indeed a lot of good example of how misuse of big data algorithms can wreak havoc among society. The problem is that the author indignation push her away from what should have been the main subject of the book. 

In the course of the book, the author raise a lot of recurring problem with WMD, like the "Flock of the feathers" generalization, the "self-fulfilling" prediction, the "discriminating proxy variable ", the "non-appealable conclusion" problem, the "non-measurable important factor". But those categories of problem, which, in my opinion, should have been the focus of the book, take a backseat toward the real subject of the book: how much the United State has social problems.

Each chapter is written to for denounce a specific social problem in the US, like predatory ads toward the poor, racial discrimination toward minority, terrible working hour among low wage workers, and so on. Some of those subjects are indeed caused by WMD. But for some, the link with the purported subject of the book is a bit strenuous. In some case, the author even exclaims "well, that has nothing to do with WMD of course". And a lot of time, WMD are not the root cause of the problem, they only exacerbate an existing one. 

That leave you with a book that is more like a classical sociology book denouncing the ill of the American society, with some talk about big data sprinkled on top. If, like me, you are not an American, you may feel a bit left out by that book. This is a shame, because by refocusing the book on the generic problem caused by WMD that I described above, the book could have had a much broader appeal. Don't get me wrong: The problem O Neil talk about ARE important social problem. But they are very specific to her own country, and the militant tone can become grating. I felt at time that the author was not explaining to me how WMD work and how to deal with them, but was rather trying to force her opinion of how the world should be over me. She was dictating me how I should think, rather than helping me shape my own opinion.

In the end, I would have preferred a more objective tone and a better focus on WMD themselves, with conclusion that can be applied more broadly to everyone, not just US citizens.

42 of 45 people found this review helpful

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  • Derek
  • 2016-09-13

a must read for the modern economy

O'Neil makes a strong case for the increasing importance of ethics in data science. The evidence for discrimination, whether intentional or not, is compelling. This book is a must for data professionals and anyone concerned with growing inequality in the economy.

6 of 7 people found this review helpful

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  • k
  • 2016-09-06

Superb narration, beautifully written.

This is a must read! I thoroughly enjoyed the real world examples of how everything I do is a data point that is being used against me.

9 of 11 people found this review helpful

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  • Trevor Flores
  • 2017-09-29

Makes you think...

Who would have though a book about mathematical models would be so interesting and enjoyable. The author will make you thiink a lot about how much they are used in your own life and it is in some cases, sobering.

2 of 2 people found this review helpful

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  • Arseny
  • 2017-05-30

High-level banter of Occupy Wall Street minded author

I thought there would be at least something about the math. Nope. If I could recommend a better read / audible that would be "Algorithms To Live By" book.

11 of 14 people found this review helpful

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  • loveamazon
  • 2019-04-04

Masterful story telling watered down by militant socialism

Yes, I’d still recommend it BUT if your not a hardcore socialist maybe make it a library rental rather than a purchase.

The socialist perspective of the author and the intentional forcing of that opinion down the reader’s throat is a HUGE unnecessary distraction from what otherwise is a very rich, compelling and well told story. I kept rooting for her to let go of the chip on her shoulder and stick to the rockstar story, but sadly no, she could not let it go and it was a distraction around every corner.

1 of 1 people found this review helpful

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  • Philomath
  • 2017-11-26

Progression of the Algorithm and where it goes wrong

Very interesting look at algorithms that fail, and fail miserably they do. It is the scary future where computer semi artificial intelligence are beginning to guide important choices.

This book shows by example how big date when used can have unintended consequences or goals that are aligned with special interest and diverge from society's interest.

Algorithms are the precursor to AI, reinforced, deep, and supervised learning. It is quite uncanny how the author at this early stage predicted the problems of the "Black Box" of algorithms, where the complexity of computation is almost impossible to decipher.

A very important book to understand how big data and algorithms to use this data can have large scale unintended consequences. It is even more important to understand when they diverge from the interest of the good and are used purely for selfish and money making or saving schemes forgetting the people it affects.

Expect more books like this as we ascend to a future of information gathering at a colossal scale and AI that has potential to know too much. Excellent read, but a little out of date.

1 of 1 people found this review helpful

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  • Victor L. Marsh, II
  • 2017-09-14

Engagingly told

This is an excellent introduction to the practical impact of mathematical models in modern society. It's not just about the economic sectors, but also judicial, and in education too. The author has a point of view, but at least address other ways of interpreting things directly (and convincingly, I think).

For future directions: there are challenges facing both the left and the right in terms of acting on the recommendations of this excellent book. Both sides claim they want people to have freedom. Ironically, the most tech-friendly folks (the left) are also least concerned about its monopoly power. On the other side, the most freedom-loving folks (the right) are also least concerned about locking up minorities or unfairly punishing teachers with bad math models.

What remains is a pathway in which both sides are hoodwinked into believing that the author's bold ideas might serve their worst biases. That's always a tall order in public policy. It's a worthy future project for those who have the technical skills and political connections to act on the author's excellent recommendations and well-argued perspectives.

1 of 1 people found this review helpful

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  • K. Donckels
  • 2017-08-23

Fascinating and Timely Subject

Delves into the discipline of meta data mining performed by computer algorithms in laymen terms.

1 of 1 people found this review helpful

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  • daniel villars
  • 2019-04-08

interesting topic highly prejudiced analysis

the writer has a good knowledge of the topic. She could have made a thorough an interesting analysis of it. however she ends up being highly biased and presents opinion rather than analysis. there there is no balance nor any counter argument presented.