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Weapons of math destruction :how big data increases inequality and threatens democracy /
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書名 ： Weapons of math destruction :how big data increases inequality and threatens democracy /
紀錄類型 ： 書目-語言資料,印刷品: 單行本
正題名[資料類型標示]/作者 ： Weapons of math destruction :Cathy O'Neil.
其他題名 ： how big data increases inequality and threatens democracy /
作者 ： O'Neil, Cathy.
版本項 ： First edition.
出版者 ： New York :Crown,[2017]
面頁冊數 ： xii, 275 pages ;21 cm.
內容註 ： Bomb parts: What is a model? -- Shell shocked: My journey of disillusionment -- Arms race: Going to college -- Propaganda machine: Online advertising -- Civilian casualties: Justice in the age of big data -- Ineligible to serve: Getting a job -- Sweating bullets: On the job -- Collateral damage: Landing credit -- No safe zone: Getting insurance -- The targeted citizen: Civic life.
標題 ： Big data
標題 ： United States
ISBN ： 9780553418835 (pbk.) :
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100 1 $aO'Neil, Cathy.
245 10$aWeapons of math destruction :$bhow big data increases inequality and threatens democracy /$cCathy O'Neil.
250 $aFirst edition.
260 $aNew York :$bCrown,$c[2017]
300 $axii, 275 pages ;$c21 cm.
504 $aIncludes bibliographical references (pages 219-252) and index.
505 0 $aBomb parts: What is a model? -- Shell shocked: My journey of disillusionment -- Arms race: Going to college -- Propaganda machine: Online advertising -- Civilian casualties: Justice in the age of big data -- Ineligible to serve: Getting a job -- Sweating bullets: On the job -- Collateral damage: Landing credit -- No safe zone: Getting insurance -- The targeted citizen: Civic life.
520 $aWe live in the age of the algorithm. Increasingly, the decisions that affect our lives -- where we go to school, whether we get a car loan, how much we pay for health insurance -- are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated. But as Cathy O'Neil reveals in this book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination: If a poor student can't get a loan because a lending model deems him too risky (by virtue of his zip code), he's then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a 'toxic cocktail for democracy.' Welcome to the dark side of Big Data. Tracing the arc of a person's life, O'Neil exposes the black box models that shape our future, both as individuals and as a society. These 'weapons of math destruction' score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target v
650 0$aBig data$xSocial aspects$zUnited States.
650 0$aBig data$xPolitical aspects$zUnited States.
650 0$aSocial indicators$xMathematical models$xMoral and ethical aspects.
650 0$aDemocracy$zUnited States.
651 0$aUnited States$xSocial conditions$y21st century.
651 1$aUnited States$xSocial conditions$x21st century.
653 $a青少年