Weapons of Math Destruction
 First edition | |
| Author | Cathy O'Neil |
|---|---|
| Language | English |
| Subject | Mathematics, race, ethnicity |
| Genre | Non-fiction |
| Publisher | Crown Books |
Publication date | 2016 |
| Publication place | United States |
| Awards | Euler Book Prize |
| ISBN | 0553418815 |
Weapons of Math Destruction is a 2016 American book about the societal impact of algorithms, written by Cathy O'Neil. It explores how some big data algorithms are increasingly used in ways that reinforce preexisting inequality. It was longlisted for the 2016 National Book Award for Nonfiction but did not make it through the shortlist.[1][2][3] The book has been widely reviewed,[4] and won the Euler Book Prize.
Overview
[edit]O'Neil, a mathematician, analyses how the use of big data and algorithms in a variety of fields, including insurance, advertising, education, and policing, can lead to decisions that harm the poor, reinforce racism, and amplify inequality. According to National Book Foundation:[1]
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."
She posits that these problematic mathematical tools share three key features: they are opaque, unregulated, and difficult to contest. They are also scalable, thereby amplifying any inherent biases to affect increasingly larger populations. WMDs, or Weapons of Math Destruction, are mathematical algorithms that supposedly take human traits and quantify them, resulting in damaging effects and the perpetuation of bias against certain groups of people.
Reception
[edit]The book received widespread praise for elucidating the consequences of reliance on big data models for structuring socioeconomic resources. Clay Shirky from The New York Times Book Review said "O'Neil does a masterly job explaining the pervasiveness and risks of the algorithms that regulate our lives," while pointing out that "the section on solutions is weaker than the illustration of the problem".[5] Kirkus Reviews praised the book for being "an unusually lucid and readable" discussion of a technical subject.[6]
In 2019, the book won the Euler Book Prize of the Mathematical Association of America.[7]
References
[edit]- ^ a b 2016 National Book Award Longlist, Nonfiction, National Book Foundation
- ^ "The National Book Awards Longlist: Nonfiction", The New Yorker, September 14, 2016
- ^ Rawlins, Aimee (September 6, 2016), Math is racist: How data is driving inequality, CNN
- ^ See:
- Lozano, Guadalupe I., "Review of Weapons of Math Destruction", MathSciNet, MR 3561130
- Braga, Filipe Meirelles Ferreira (June 2016), "Review of Weapons of Math Destruction", Mural Internacional, 7 (1), doi:10.12957/rmi.2016.25939
- Lamb, Evelyn (August 2016), "Review of Weapons of Math Destruction", Roots of Unity, Scientific American
- Shankar, Kalpana (September 2016), "A data scientist reveals how invisible algorithms perpetuate inequality (review of Weapons of Math Destruction)", Science
- Doctorow, Cory (September 2016), "Weapons of Math Destruction: invisible, ubiquitous algorithms are ruining millions of lives", BoingBoing
- McEvers, Kelly (September 2016), "'Weapons Of Math Destruction' outlines dangers of relying on data analytics", All Things Considered, NPR
- Hayden, Robert W. (January 2017), "Review of Weapons of Math Destruction", MAA Reviews
- Varis, Piia (January 2017), "Review of Weapons of Math Destruction", Diggit
- Omitola, Tope (January 2017), "Review of Weapons of Math Destruction", ACM Computing Reviews
- Jain, Apurv (March 2017), "Review of Weapons of Math Destruction", Business Economics, 52 (2): 123–125, doi:10.1057/s11369-017-0027-3, S2CID 157914174
- Schrag, Francis (March 2017), "Review of Weapons of Math Destruction", Education Review, 24, doi:10.14507/er.v24.2197
- Bradley, James (March 2017), "Review of Weapons of Math Destruction", Perspectives on Science and Christian Faith, 69 (1): 54
- Maloney, Cory (Spring 2017), "Review of Weapons of Math Destruction", Journal of Markets & Morality, 20 (1): 194
- Roy, Michael (April 2017), "Review of Weapons of Math Destruction", College & Research Libraries, 78 (3): 403, doi:10.5860/crl.78.3.403
- Case, James (May 2017), "When big data algorithms discriminate (review of Weapons of Math Destruction", SIAM News, 50 (4)
- Arslan, Faruk (July 2017), "Review of Weapons of Math Destruction", Journal of Information Privacy and Security, 13 (3): 157–159, doi:10.1080/15536548.2017.1357388, S2CID 188383106
- Poovey, Mary (September 2017), "Review of Weapons of Math Destruction", Notices of the American Mathematical Society, 64 (8): 933–935, doi:10.1090/noti1561
- Doyle, Tony (October 2017), "Review of Weapons of Math Destruction", The Information Society, 33 (5): 301–302, doi:10.1080/01972243.2017.1354593, S2CID 22283226
- Mateen, Harris (2018), "Review of Weapons of Math Destruction", Berkeley Journal of Employment and Labor Law, 39 (1): 285–292
- Tunstall, Samuel (January 2018), "Models as weapons (review of Weapons of Math Destruction", Numeracy, 11 (1), doi:10.5038/1936-4660.11.1.10
- Woodson, Thomas (August 2018), "Review of Weapons of Math Destruction", Journal of Responsible Innovation, 5 (3): 361–363, doi:10.1080/23299460.2018.1495027
- Bansal, Gaurav (January 2019), "Review of Weapons of Math Destruction", Journal of Information Technology Case and Application Research, 21 (1): 60–63, doi:10.1080/15228053.2019.1587571, S2CID 189618193
- Verma, Shikha (June 2019), "Review of Weapons of Math Destruction", Vikalpa: The Journal for Decision Makers, 44 (2): 97–98, doi:10.1177/0256090919853933
- Eusufzai, Zaki (September 2019), "Review of Weapons of Math Destruction", The Social Science Journal, 56 (3): 425–426, doi:10.1016/j.soscij.2019.04.002, S2CID 203099077
- ^ Shirky, Clay (October 3, 2016), "Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy", The New York Times Book Review
- ^ "Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy", Kirkus Reviews, July 19, 2016
- ^ "Euler Book Prize" (PDF), Prizes and Awards, Joint Mathematics Meetings, pp. 3–4, January 2019, retrieved 2019-07-20 – via American Mathematical Society
External links
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