Weapons of Math Destruction

how big data increases inequality and threatens democracy

Paperback, 259 pages

English language

Published April 28, 2016 by Allen Lane.

ISBN:
9780241296813
OCLC Number:
958464372

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4 stars (12 reviews)

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 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 …

6 editions

Suit up for Combat!

5 stars

This was an exceptional book. It's not heavy into statistics but gives the rationale for what is a WMD (Weapon of Math Destruction) and WMDs maybe a new term but we have been under the exploitation of WMDs well before we think. It's not a new phenomenon but it is one that we should be aware of.

Take a read and learn how about them so that we can all do better to combat them and use math to not only help describe the world but make it a better place to live in.

Review of 'Weapons of Math Destruction' on 'Storygraph'

5 stars

Excellent discussion on how the use of algorithms is affecting our education system, how likely are we to be hired, how much we pay for insurance and mortgages. These models have become black boxes that nobody knows exactly how they work but are considered reliable. What few people realize is that these algorithms are reinforcing discrimination and have biases built in them. So, instead of a fair objective system to evaluate whatever (loan approvals, credit scores, job candidates, school teacher's performance, etc), we have opaque models being applied everywhere that cannot be disputed or even understood. It's scary to think that our future life decisions will rely on algorithms.

Review of 'Weapons of Math Destruction' on 'Goodreads'

4 stars

I, too, was a mathematician once, but I lost my faith. Ms. O'Neil still seems to have much of hers, for an Occupier. I kept thinking she was naive that this stuff is fixable, but I may just be naively paranoid.

That algorithms can be biased was not a surprise to me. Logic itself can be biased because it is dependent on language which, like many WMDs, is a black box. It is full of proxies. Take the term "criminal" which (like "terrorist") brands the one so called as an evil doer. And it's measurable by determining if one has been convicted of anything. You can read [b:The New Jim Crow: Mass Incarceration in the Age of Colorblindness|6792458|The New Jim Crow Mass Incarceration in the Age of Colorblindness|Michelle Alexander|https://images.gr-assets.com/books/1328751532s/6792458.jpg|6996712] and discover that going to jail is part of systemic racism but when you hear the word "criminal" or "convict", you …

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Subjects

  • Big data
  • Social aspects
  • Human behavior
  • Mathematical models
  • Algorithms
  • Données volumineuses
  • Aspect social
  • Comportement humain
  • Modèles mathématiques
  • Algorithmes