Record ID | marc_openlibraries_sanfranciscopubliclibrary/sfpl_chq_2018_12_24_run05.mrc:366956408:10111 |
Source | marc_openlibraries_sanfranciscopubliclibrary |
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008 160315s2016 nyu b 001 0 eng
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035 $a(OCoLC)932385614$z(OCoLC)957230777
037 $bRandom House Inc, Attn Order Entry 400 Hahn rd, Westminster, MD, USA, 21157$nSAN 201-3975
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100 1 $aO'Neil, Cathy,$eauthor.
245 10 $aWeapons of math destruction :$bhow big data increases inequality and threatens democracy /$cCathy O'Neil.
250 $aFirst edition.
264 1 $aNew York :$bCrown,$c[2016]
300 $ax, 259 pages ;$c22 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
338 $avolume$bnc$2rdacarrier
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 $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 résumés, 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."--Dust jacket.
504 $aIncludes bibliographical references (pages 219-252) and index.
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.
776 08 $iOnline version:$aO'Neil, Cathy, author.$tWeapons of math destruction.$bFirst edition.$dNew York : Crown Publishers, [2016]$z9780553418828$w(DLC) 2016016487
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