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

Increasingly, the decisions that affect our lives—where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. But in the end, it’s up to us to become more savvy about the models that govern our lives. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.” Welcome to the dark side of Big Data.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. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his zip code), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. This important book empowers us to ask the tough questions, uncover the truth, and demand change.— Longlist for National Book Award (Non-Fiction)— Goodreads, semi-finalist for the 2016 Goodreads Choice Awards (Science and Technology)&mdash

Amazon Customer said Stop Using Math as a Weapon. So here you are on Amazon's web page, reading about Cathy O'Neil's new book, Weapons of Math Destruction. Amazon hopes you buy the book (and so do I, it's great!). But Amazon also hopes it can sell you some other books while you're here. That's why, in a prominent plac. CodeMaster Talon said "They back up their analysis with reams of statistics, which give them the studied air of evenhanded science.". I struggled with the star rating for this book. There are certainly aspects of the work that merit five stars. And it is VERY thought-provoking, like a good book should be. But there are flaws, significant ones, with the biggest flaw being a glaring over-simplification. "WMD offered insights into some of the threats posed by Big Data" according to Tim. The book looks at the black box algorithms and their misuses. It starts strong, but becomes a repeat of the same story line in late chapters. It definitely gave background of the dangers of Big Data in a number of industries, and painted the grim picture of how this is

Strangelove or Catch-22. This makes for a remarkably page-turning read for a book about algorithms. Bonus points: it’s accessible, compelling, and—something I wasn’t expecting—really fun to read.”—Inside Higher Ed“Often we don’t even know where to look for those important algorithms, because by definition the most dangerous ones are also the most secretive. a thought-provoking read for anyone inclined to believe that data doesn't lie.”—Reuters“This is a manual

She then worked as a data scientist at various start-ups, building models that predict people’s purchases and clicks. 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. . Cathy O'Neil is a data scientist and author of the blog mathbabe. E. Shaw. O’Neil started the Lede Program in Data Journalism at Columbia and is the