Algorithms of Oppression: How Search Engines Reinforce Racism

Safiya Umoja Noble

  • 出版商: NYU Press
  • 出版日期: 2018-02-20
  • 售價: $1,350
  • 貴賓價: 9.5$1,283
  • 語言: 英文
  • 頁數: 256
  • 裝訂: Paperback
  • ISBN: 1479837245
  • ISBN-13: 9781479837243
  • 相關分類: 資料結構與演算法

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A revealing look at how negative biases against women of color are embedded in search engine results and algorithms
 
Run a Google search for “black girls”—what will you find? “Big Booty” and other sexually explicit terms are likely to come up as top search terms. But, if you type in “white girls,” the results are radically different. The suggested porn sites and un-moderated discussions about “why black women are so sassy” or “why black women are so angry” presents a disturbing portrait of black womanhood in modern society.
 
In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color.
 
Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance—operating as a source for email, a major vehicle for primary and secondary school learning, and beyond—understanding and reversing these disquieting trends and discriminatory practices is of utmost importance.
 
An original, surprising and, at times, disturbing account of bias on the internet, Algorithms of Oppression contributes to our understanding of how racism is created, maintained, and disseminated in the 21st century.
 
Safiya Noble discusses search engine bias in an interview with USC Annenberg School for Communication and Journalism