Weapons of Math Destruction

How Big Data Increases Inequality and Threatens Democracy

De: Cathy O'Neil

Narrado por: Cathy O'Neil

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 Globe • Wired • 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.

interesting read

very interesting. this woman's view on the world and how big data affects us are very compelling.

Eye-opening research!

This book is a must read for data scientists, students, policy makers and others who need a balanced view of the implications of our increasingly data-driven world.

Intriguing

While intriguing and insightful, in some instances the author may suffer from her own confirmation bias (an issue she attacks in the book). It's worth the listen, do not treat this book, or it's biases, as doctrine.

decent concept

authors recommended solutions are just political dispositions and aren't thought through related to her useful points.

Not bad, but...

I found it tiresome to listen to the narrator say WMDs so many times. I get the arguments, but perhaps she could've dug deeper on the ethics analysis rather than just on poverty and race variables.