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

ISBN-13: 9780553418835 / Angielski / Miękka / 2017 / 288 str.

Cathy O'Neil
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy Cathy O'Neil 9780553418835 Broadway Books - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

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

ISBN-13: 9780553418835 / Angielski / Miękka / 2017 / 288 str.

Cathy O'Neil
cena 76,86 zł
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Longlisted for the National Book Award
New York Times Bestseller

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 car loan, how much we pay for health 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.

But as Cathy O'Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they're wrong. 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. 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. These "weapons of math destruction" score teachers and students, sort resumes, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health.

O'Neil calls on modelers 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.

-- Longlist for National Book Award (Non-Fiction)
-- Goodreads, semi-finalist for the 2016 Goodreads Choice Awards (Science and Technology)
-- Kirkus, Best Books of 2016
-- New York Times, 100 Notable Books of 2016 (Non-Fiction)
-- The Guardian, Best Books of 2016
-- WBUR's "On Point," Best Books of 2016: Staff Picks
-- Boston Globe, Best Books of 2016, Non-Fiction

Kategorie:
Nauka
Kategorie BISAC:
Political Science > Public Policy - General
Social Science > Privacy & Surveillance (see also Political Science - Privacy & Surveillance
Business & Economics > Statystyka gospodarcza
Wydawca:
Broadway Books
Język:
Angielski
ISBN-13:
9780553418835
Rok wydania:
2017
Ilość stron:
288
Waga:
0.20 kg
Wymiary:
19.56 x 12.95 x 1.78
Oprawa:
Miękka
Wolumenów:
01
Dodatkowe informacje:
Bibliografia

O Neil s book offers a frightening look at how algorithms are increasingly regulating people. . . . Her knowledge of the power and risks of mathematical models, coupled with a gift for analogy, makes her one of the most valuable observers of the continuing weaponization of big data. . . . [She] does a masterly job explaining the pervasiveness and risks of the algorithms that regulate our lives. The New York Times Book Review

"Weapons of Math Destruction is the Big Data story Silicon Valley proponents won't tell. . . . [It] pithily exposes flaws in how information is used to assess everything from creditworthiness to policing tactics . . . a thought-provoking read for anyone inclined to believe that data doesn't lie. Reuters

This is a manual for the twenty-first century citizen, and it succeeds where other big data accounts have failed it is accessible, refreshingly critical and feels relevant and urgent. Financial Times

"Insightful and disturbing." New York Review of Books

Weapons of Math Destruction is an urgent critique of . . . the rampant misuse of math in nearly every aspect of our lives. Boston Globe

A fascinating and deeply disturbing book. Yuval Noah Harari, author of Sapiens

Illuminating . . . [O Neil] makes a convincing case that this reliance on algorithms has gone too far. The Atlantic

A nuanced reminder that big data is only as good as the people wielding it. Wired

If you ve ever suspected there was something baleful about our deep trust in data, but lacked the mathematical skills to figure out exactly what it was, this is the book for you. Salon

O Neil is an ideal person to write this book. She is an academic mathematician turned Wall Street quant turned data scientist who has been involved in Occupy Wall Street and recently started an algorithmic auditing company. She is one of the strongest voices speaking out for limiting the ways we allow algorithms to influence our lives. . . . While Weapons of Math Destruction is full of hard truths and grim statistics, it is also accessible and even entertaining. O Neil s writing is direct and easy to read I devoured it in an afternoon. Scientific American

Indispensable . . . Despite the technical complexity of its subject, Weapons of Math Destruction lucidly guides readers through these complex modeling systems. . . . O Neil s book is an excellent primer on the ethical and moral risks of Big Data and an algorithmically dependent world. . . . For those curious about how Big Data can help them and their businesses, or how it has been reshaping the world around them, Weapons of Math Destruction is an essential starting place. National Post

Cathy O Neil has seen Big Data from the inside, and the picture isn t pretty. Weapons of Math Destruction opens the curtain on algorithms that exploit people and distort the truth while posing as neutral mathematical tools. This book is wise, fierce, and desperately necessary. Jordan Ellenberg, University of Wisconsin-Madison, author of How Not To Be Wrong

O Neil has become [a whistle-blower] for the world of Big Data . . . [in] her important new book. . . .  Her work makes particularly disturbing points about how being on the wrong side of an algorithmic decision can snowball in incredibly destructive ways. Time

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 is currently a columnist for Bloomberg View.



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