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

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Penguin Books, Limited, 2016 - Algorithms - 259 pages
21 Reviews
We live in the age of the algorithm. Increasingly, the decisions that affect our lives - whether we get a job or a loan, how much we pay for insurance - are being made 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. These models are opaque, unregulated, and incontestable, even when they're wrong. Most troubling, they reinforce discrimination, creating a toxic cocktail for democracy. Tracing the arc of a person's life, Cathy O'Neil exposes the black box models that shape our future 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'Neilcalls 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.

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LibraryThing Review

User Review  - calmclam - www.librarything.com

I thought this was a very interesting discussion of the risks of AI algorithms. In particular, the discussions about transparency and accountability are very interesting and disturbing. Read full review

LibraryThing Review

User Review  - quaintlittlehead - LibraryThing

"Weapons of Math Destruction" lays out a number of clear and creepy cases of how predictive algorithms get things wrong, with negative and, in some cases, infuriating consequences. O'Neil walks ... Read full review

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About the author (2016)

Cathy O'Neil is a data scientist and author of the blog mathbabe.org. She earned a Ph.D. in mathematics from Harvard and taught at Barnard College before moving to the private sector, where she worked for the hedge fund D. E. Shaw. She then worked as a data scientist at various start-ups, building models that predict people's purchases and clicks. O'Neil started the Lede Program in Data Journalism at Columbia and is the author of Doing Data Science. She appears weekly on the Slate Money podcast.

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