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Weapons of Math Destruction

How Big Data Increases Inequality and Threatens Democracy

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Weapons of Math Destruction

Auteur(s): Cathy O'Neil
Narrateur(s): Cathy O'Neil
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À propos de cet audio

NEW YORK TIMES BESTSELLER A former Wall Street quant sounds the alarm on Big Data and the mathematical models that threaten to rip apart our social fabric—with a new afterword

“A manual for the twenty-first-century citizen . . . relevant and urgent.”—Financial Times

NATIONAL BOOK AWARD LONGLIST • NAMED ONE OF THE BEST BOOKS OF THE YEAR BY The New York Times Book Review The Boston GlobeWired Fortune Kirkus Reviews The Guardian Nature On Point

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’Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination—propping up the lucky, punishing the downtrodden, and undermining our democracy in the process. Welcome to the dark side of Big Data.

©2016 Cathy O'Neil (P)2016 Random House Audio
Politiques publiques Sciences sociales Économie Entreprise Wall Street Business Math
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Ce que les critiques en disent

“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.”—The 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.”Reuters

“This is a manual for the twenty-first century citizen, and it succeeds where other big data accounts have failedit is accessible, refreshingly critical and feels relevant and urgent.”—Financial Times

Ce que les auditeurs disent de Weapons of Math Destruction

Moyenne des évaluations de clients
Au global
  • 4.5 out of 5 stars
  • 5 étoiles
    75
  • 4 étoiles
    26
  • 3 étoiles
    9
  • 2 étoiles
    2
  • 1 étoile
    2
Performance
  • 4.5 out of 5 stars
  • 5 étoiles
    71
  • 4 étoiles
    18
  • 3 étoiles
    6
  • 2 étoiles
    1
  • 1 étoile
    1
Histoire
  • 4.5 out of 5 stars
  • 5 étoiles
    60
  • 4 étoiles
    27
  • 3 étoiles
    5
  • 2 étoiles
    2
  • 1 étoile
    2

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  • Au global
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Histoire
    5 out of 5 stars

A must read

This is a very important, informative, and easy to comprehend read, written in a very conversational style. If it doesn’t get you mad or concerned then you didn’t read it. Which I insist you do, read.

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  • Au global
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Histoire
    5 out of 5 stars

Brilliant analysis soon to be commonplace

This book spoke about things I had no idea about until I heard it. Now I see her point everywhere. Just more ways that a noose is drawing in around an unsuspecting publics neck . Definitely a worthwhile read

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  • Au global
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Histoire
    5 out of 5 stars

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.

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1 personne a trouvé cela utile

  • Au global
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Histoire
    5 out of 5 stars

must read for all

what a wonderful book showing the decide of rich and poor. she did a great job showing the direction of misused data is having on the struggling how how the math is forcing and keeping people down. determination use to account for something but when the numbers are all you are it makes it all the harder.

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  • Au global
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Histoire
    5 out of 5 stars

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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  • Au global
    3 out of 5 stars
  • Performance
    4 out of 5 stars
  • Histoire
    3 out of 5 stars

Entertaining read

A bit left leaning but I still enjoyed it, lots of good stories too, recommend it

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  • Au global
    1 out of 5 stars
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    5 out of 5 stars
  • Histoire
    1 out of 5 stars

What was that...

Mess of ideas. Should have just stuck to commentary on misuse of mathematical concepts.
The attempted political was strange and unnecessary (random comments about race and social constructs just thrown into a book supposedly focusing on the misuse of ... whatever this book thought it was about)
Social commentary was out of context and unfounded.
Sweeping claims about ML, its current state and potential future were just thrown in there, haphazardly throwing out concepts entire books are dedicated to.
Critisism of big tech companies was generic and shallow. Content I expect on someone's Facebook feed.

Second chapter is the only one worth listening to.

Complaining is easy, proposing solutions were hard.

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