HemGrupperDiskuteraMerTidsandan
Sök igenom hela webbplatsen
Denna webbplats använder kakor för att fungera optimalt, analysera användarbeteende och för att visa reklam (om du inte är inloggad). Genom att använda LibraryThing intygar du att du har läst och förstått våra Regler och integritetspolicy. All användning av denna webbplats lyder under dessa regler.
Hide this

Resultat från Google Book Search

Klicka på en bild för att gå till Google Book Search.

Weapons of math destruction : how big data…
Laddar...

Weapons of math destruction : how big data increases inequality and… (utgåvan 2016)

av Cathy O'Neil

MedlemmarRecensionerPopularitetGenomsnittligt betygOmnämnanden
1,1856912,587 (3.84)48
Longlisted for the National Book AwardNew 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 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. -- 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… (mer)
Medlem:boisjere
Titel:Weapons of math destruction : how big data increases inequality and threatens democracy
Författare:Cathy O'Neil
Info:New York : Crown, [2016]
Samlingar:Ditt bibliotek
Betyg:
Taggar:Ingen/inga

Verkdetaljer

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy av Cathy O'Neil

Senast inlagd avprivat bibliotek, ccatalfo, Gadi_Cohen, royragsdale, marlet23, PWAdelaide, iaross, dono421846, MadHun
Laddar...

Gå med i LibraryThing för att få reda på om du skulle tycka om den här boken.

Det finns inga diskussioner på LibraryThing om den här boken.

» Se även 48 omnämnanden

engelska (69)  italienska (1)  nederländska (1)  ungerska (1)  tyska (1)  Alla språk (73)
Visa 1-5 av 73 (nästa | visa alla)
Loved this book- it was a class assignment and I learned a lot about Big Data. ( )
  Nikki_Sojkowski | Aug 26, 2021 |
A very timely, detailed, and expert (yet highly readable) look at the damaging potentials of using algorithms to regulate our lives. This absolutely relevant book is a must-read for anyone involved in data science or simply algorithm users.
Using a clear definition of what constitutes WMDs, (opacity, negative feedback loops, no absence of feedback, they tend to punish the poor, model = black box). O'Neil goes through a wide range of social institutions (health, education, work, politics, criminal justice, to name a few) and examines the damages done by WMDs. My own personal distaste for work wellness stuff felt very validated.
In the end, O'Neil offers suggestions as to what can be done to "tame" WMDs and reduce their damage (including trading some efficiency for fairness), or better, use the same techniques made available thanks to Big Data for socially productive purposes. ( )
  SocProf9740 | Jul 11, 2021 |
In this relatively brief book, Cathy O'Neil (a former professor and hedge fund quant) reviews the way in which data analysis can be misused--from the US News and World Report college ranking, to evaluations, to insurance. There are multiple potential problems: data that is flatly inaccurate (garbage in, garbage out); data that doesn't track well with outcomes (using secondary measures, as in teacher evaluations); poor algorithms (personality tests for job hiring); proxies that result in racism or classism (targeting based on location or peer group); and opacity.

I've read some of the criticisms of the book. Even though O'Neil calls for the human touch at the end, she does not deny that humans are biased. She also acknowledges that data analysis and algorithms are valuable. In some cases, data analysis can remove bias. But in others, it replicates the bias of the people who create the algorithms and can create a feedback loop by which an algorithm perpetuates that bias. It is not an in depth, mathematically oriented approach. I was aware of many of the issues from popular news articles. But it's not data scientists she's trying to convince here--she's trying to show the public what the problems are with data that is collected and analyzed, often without the knowledge of the people it's being collected from.

It's a nice, approachable introduction to the issues, and doesn't require any particular knowledge of math to understand. ( )
  arosoff | Jul 11, 2021 |
Highlights some really important issues with current applications of big data, but felt a little one-sided and superficial. ( )
  MysteryTea | Jun 14, 2021 |
In ihrem Buch, das im Original „Weapons of Math Destruction“ heißt, beschreibt die Mathematikerin Cathy O'Neil die wenig segensreichen Aspekte der Nutzung von Big Data. Im Grunde kann ich zwei große Aspekte ausmachen: Zum einen die Entstehung der Daten: Beim Sammeln bzw. auch der Auswahl von Daten kommen natürlich menschliche Fehler, Vorurteile zum Tragen. Es ist ja zudem auch eine Frage, welche Daten überhaupt verfügbar sind. Schwarze Menschen werden beispielsweise höchst signifikant öfter von der Polizei kontrolliert, fallen öfter in die Kriminalstatistik, auch für Bagatelldelikte, wohingegen in weißen Vororten eine ähnliche Form der Kontrolle nicht stattfindet, obwohl es diese Bagatelldelikte genau so gibt. Und die richtig große Kriminalität in Formen und Banken taucht in keiner Statistik auf. Daraus resultiert aber eine Verzerrung in der Kriminalstatistik, in der Prognose von Straftaten, ganz zu schweigen von der Mühe des alltäglichen Lebens unter Generalverdacht.
Welche Daten in große Datenauswertungen fallen, ist ebenfalls oftmals ein Rätsel, so zum Beispiel bei den wirklich extrem wirksamen Uni-Rankings durch amerikanische Medien.
Andererseits ist natürlich die Nutzung der Daten ein ethisches Problem, wie schon bei der obigen Auswertung der Kriminalstatistik deutlich wird, aber zum Beispiel auch bei der Jobsuche – vor allem, wenn es in den Daten namensgleiche und vll, sogar am selben Tag geborene Menschen gibt und Verwechslungen vorkommen.
Die Autorin nennt viele Bereiche, in denen die Big Data als „Weapon of Math Destruction“ wirkt. Bei vielen der Beispiele, die Cathy O'Neil in ihrem Buch schildert, kann man sich zum Glück denken, dass das in Deutschland nicht passieren kann. Und das liegt daran, dass hier doch vieles staatlich reglementiert ist (z.B. das Universitätssystem) – dies an die Adresse derjenigen, die immer von zu vielen Verboten faseln. Wo alles freigegeben ist, gewinnen halt in der Regel nicht die Schwachen. Dennoch sind viele der Beispiele erschreckend plausibel und auch hier möglich und stattfindend. ( )
  Wassilissa | May 7, 2021 |
Visa 1-5 av 73 (nästa | visa alla)
inga recensioner | lägg till en recension

» Lägg till fler författare (9 möjliga)

Författarens namnRollTyp av författareVerk?Status
Cathy O'Neilprimär författarealla utgåvorberäknat
Marty, SébastienÖversättaremedförfattarevissa utgåvorbekräftat
Villani, CédricFörordmedförfattarevissa utgåvorbekräftat
Du måste logga in för att ändra Allmänna fakta.
Mer hjälp finns på hjälpsidan för Allmänna fakta.
Vedertagen titel
Originaltitel
Alternativa titlar
Första utgivningsdatum
Personer/gestalter
Viktiga platser
Viktiga händelser
Information från den engelska sidan med allmänna fakta. Redigera om du vill anpassa till ditt språk.
Relaterade filmer
Priser och utmärkelser
Information från den engelska sidan med allmänna fakta. Redigera om du vill anpassa till ditt språk.
Motto
Dedikation
Information från den engelska sidan med allmänna fakta. Redigera om du vill anpassa till ditt språk.
This book is dedicated to all the underdogs
Inledande ord
Information från den engelska sidan med allmänna fakta. Redigera om du vill anpassa till ditt språk.
When I was a little girl, I used to gaze at the traffic out the car window and study the numbers on license plate.
Citat
Avslutande ord
Information från den engelska sidan med allmänna fakta. Redigera om du vill anpassa till ditt språk.
(Klicka för att visa. Varning: Kan innehålla spoilers.)
Särskiljningsnotis
Förlagets redaktörer
På omslaget citeras
Ursprungsspråk
Information från den engelska sidan med allmänna fakta. Redigera om du vill anpassa till ditt språk.
Kanonisk DDC/MDS
Kanonisk LCC

Hänvisningar till detta verk hos externa resurser.

Wikipedia på engelska

Ingen/inga

Longlisted for the National Book AwardNew 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 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. -- 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

Inga biblioteksbeskrivningar kunde hittas.

Bokbeskrivning
Haiku-sammanfattning

Populära omslag

Snabblänkar

Betyg

Medelbetyg: (3.84)
0.5
1 3
1.5
2 10
2.5 5
3 60
3.5 20
4 100
4.5 22
5 52

Är det här du?

Bli LibraryThing-författare.

 

Om | Kontakt | LibraryThing.com | Sekretess/Villkor | Hjälp/Vanliga frågor | Blogg | Butik | APIs | TinyCat | Efterlämnade bibliotek | Förhandsrecensenter | Allmänna fakta | 162,559,657 böcker! | Topplisten: Alltid synlig