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04011aam a2200541Ii 4500 001 477D53F4B5CF11EE9701991E25ECA4DB 003 SILO 005 20240118010029 008 170201r20172016enk b 001 0 eng d 020 $a 0141985410 020 $a 9780141985411 035 $a (OCoLC)991124136 040 $a NLE $b eng $e rda $c NLE $d OCLCO $d SHS $d CHVBK $d OCLCO $d OCLCQ $d BCD $d ATSHR $d OCLCF $d OCLCA $d UKMGB $d QGQ $d OCLCA $d U@M $d MM9 $d OCLCQ $d OCLCO $d UKOBU $d OCLCO $d VU@ $d OCLCO $d SILO 043 $a n-us--- 050 4 $a QA76.9.B45 082 04 $a 005.7 $2 23 084 $a 89.35 $2 bcl 100 1 $a O'Neil, Cathy, $e author. 245 10 $a Weapons of math destruction : $b how big data increases inequality and threatens democracy / $c Cathy O'Neil. 264 1 $a London : $b Penguin Books, $c 2017. 300 $a 259 pages ; $c 20 cm 500 $a Originally published: UK: Allen Lane, 2016. 504 $a Includes bibliographical references and index. 505 0 $a 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 520 $a "A former Wall Street quantitative analyst sounds an alarm on mathematical modeling, a pervasive new force in society that threatens to undermine democracy and widen inequality, "--NoveList 520 $a "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 reÌsumeÌs, 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."--Jacket 650 0 $a Big data $x Social aspects. 650 0 $a Mathematical models $x Social aspects. 650 0 $a Algorithms $x Social aspects. 650 0 $a Democracy. 650 6 $a DonneÌes volumineuses $x Aspect social. 650 6 $a ModeÌles matheÌmatiques $x Aspect social. 650 6 $a Algorithmes $x Aspect social. 650 7 $a Computers and IT. $2 eflch 650 7 $a Big data $x Social aspects $2 fast 650 7 $a Democracy $2 fast 650 7 $a Demokratie $2 gnd 650 7 $a Big Data $2 gnd 650 7 $a Kritik $2 gnd 650 7 $a Datenerhebung $2 gnd 650 7 $a Sozialer Indikator $2 gnd 650 7 $a Soziale Ungleichheit $2 gnd 651 7 $a USA $2 gnd 650 7 $a Computers and IT. $2 ukslc 941 $a 1 952 $l UNUX074 $d 20240118010522.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=477D53F4B5CF11EE9701991E25ECA4DB 994 $a Z0 $b NIUInitiate Another SILO Locator Search