The DOI matches its Crossref record.
Algorithms of Oppression: How Search Engines Reinforce Racism
Abstract
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.
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Cited by
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Consumers and artificial intelligence: An experiential perspective
Puntoni, S., Reczek, R. W., Giesler, M., & Botti, S. (2021) · Journal of Marketing · doi:10.1177/0022242920953847 · Cited by 1,547
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., Boselie, P., Lee Cooke, F., Decker, S., DeNisi, A., et al. (2023) · Human Resource Management Journal · doi:10.1111/1748-8583.12524 · Cited by 908
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Metadata
- Authors
- Noble, S. U.
- Venue
- New York University Press eBooks
- Publisher
- New York University Press
- Published
- 2020-05-22
- OpenAlex
- W2999490220
- Cited by
- 416
- References
- 0
- FWCI
- 8.18
- Type
- book
- Language
- en
- Open access
- closed
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