Weapons of Math Destruction
How Big Data Increases Inequality and Threatens Democracy
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Weapons of Math Destruction
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Narrated by:
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Cathy O'Neil
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By:
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Cathy O'Neil
About this listen
Brought to you by Penguin.
In this New York Times best seller, Cathy O'Neil, one of the first champions of algorithmic accountability, 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 loan, how much we pay for 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.
And yet, as Cathy O'Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated and incontestable, even when they're wrong. Most troubling, they reinforce discrimination. 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 CVs, grant or deny loans, evaluate workers, target voters and monitor our health.
O'Neil calls on modellers 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.
©2022 Cathy O'Neil (P)2022 Penguin AudioListeners also enjoyed...
Critic reviews
"A manual for the 21st-century citizen...accessible, refreshingly critical, relevant and urgent. (Financial Times)
"Fascinating and deeply disturbing." (Yuval Noah Harari, Guardian Books of the Year)
What listeners say about Weapons of Math Destruction
Average customer ratingsReviews - Please select the tabs below to change the source of reviews.
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Overall3 out of 5 stars
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Performance4 out of 5 stars
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Story3 out of 5 stars
- Thomas Z. Ramsoy
- 01-07-24
Too American and gpt?
Was really looking forward to this book, and the author is definitely accomplished. The book has two flaws in my view. First, it's too americanized when it would be amazing if we could have more international examples or at least more extrapolation from the examples given. It comes across as very idiosyncratic and local when the issues raised are much more general and broadly applicable. Second, a lot of the language seems eerily close to the "shame" list of words that AI models like chatGPT are producing too much of (like "delve"), and the writing can come across as a little too canned for my personal taste at times (and other times quite vivid and good, so an uneven experience). In total the book is likely good for US based readers and listeners but seems too narrow and linguistically stereotypical when the author herself has so much to give.
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- ARRON
- 26-05-23
Great listen
Read the book and now listened to the audiobook, brilliant eye opener for the head in the sand modern human
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Overall5 out of 5 stars
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- Amazon Customer
- 11-10-23
engaging and fascinating
Well written book, very engaging storytelling, fascinating topic. Recomend to anyone with any level of knowledge.
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- Ali Al-Marsumi
- 25-09-24
One of the most interesting books
I enjoyed this book from start to finish. we all know that there are flaws with data science but this book dives deep into those flaws.
great real life examples explained and analyzed with great details
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Overall5 out of 5 stars
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- PMPM
- 23-10-22
Hate math? Read this book and change your mind.
Been meaning to get hold of this book for a while having seen Cathy O’Neil in a number of interviews and been really impressed by her.
Her book lays bare the hidden truths about how data impacts our private lives as well as the gross inequalities it creates and quiet autocracy it hides.
You get an eye-opening education in to how we all are triaged by algorithms. We live in worlds were we go along in innocence not realizing just how deep the data mining of our lives goes.
Ignore O’Neils messages at your peril but know that there will be some faraway algorithms in big data land that will be noting your refusal to engage with her message for future reference. In time to come AI will use that refusal to the advantage of the entities it represents.
This isn’t conspiracy theory, O’Neil a mathematician and now data analyst who has worked as a quant backs up all her assertions with facts.
I wholeheartedly commend this book to you.
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