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Review of "Algorithms of oppression: how search engines reinforce racism," by Noble, S. U. (2018). New York, New York: NYU Press.

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Read and considered thoughtfully, Safiya Umoja Noble's Algorithms of Oppression: How Search Engines Reinforce Racism is devastating. It reduces to rubble the notion that technology is neutral and ideology-free. Noble's crushing the neutrality myth does several things. First, this act lays foundations for her argument: only if you recognize and understand that technology is built with, and integrates, bias, can you then be open to her primary thesis: search engines advance discriminatory and often racist content. Second, it banishes a convenient response for many self-identified meritocratic Silicon Valley "winners" and their supporters. Post-reading, some individuals may retain their beliefs in a neutral and ideology-free technology in spite of the overwhelming evidence and citations Noble brings to bear. Effective countering of Noble's claims is unlikely to occur. For professionals working in technology, information, argumentation, and/or rhetorical studies, Algorithms of Oppression is refreshing. Agonistic towards structural racism and its defenses, single-minded in its evidentiary presentation, collaborative in its acknowledgement of others' scholarship and research, Noble models many academic, critical, and social moves. Technology scholars and writers will find in Algorithms of Oppression a masterful mentor text on how to be an activist researcher scholar. Noble also makes this enjoyable reading. It is uncommon to find academic books that can simultaneously be read, used, and applied by academics and non-academics alike.
Association for Computing Machinery (ACM)
Title: Review of "Algorithms of oppression: how search engines reinforce racism," by Noble, S. U. (2018). New York, New York: NYU Press.
Description:
Read and considered thoughtfully, Safiya Umoja Noble's Algorithms of Oppression: How Search Engines Reinforce Racism is devastating.
It reduces to rubble the notion that technology is neutral and ideology-free.
Noble's crushing the neutrality myth does several things.
First, this act lays foundations for her argument: only if you recognize and understand that technology is built with, and integrates, bias, can you then be open to her primary thesis: search engines advance discriminatory and often racist content.
Second, it banishes a convenient response for many self-identified meritocratic Silicon Valley "winners" and their supporters.
Post-reading, some individuals may retain their beliefs in a neutral and ideology-free technology in spite of the overwhelming evidence and citations Noble brings to bear.
Effective countering of Noble's claims is unlikely to occur.
For professionals working in technology, information, argumentation, and/or rhetorical studies, Algorithms of Oppression is refreshing.
Agonistic towards structural racism and its defenses, single-minded in its evidentiary presentation, collaborative in its acknowledgement of others' scholarship and research, Noble models many academic, critical, and social moves.
Technology scholars and writers will find in Algorithms of Oppression a masterful mentor text on how to be an activist researcher scholar.
Noble also makes this enjoyable reading.
It is uncommon to find academic books that can simultaneously be read, used, and applied by academics and non-academics alike.

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