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The Bias Embedded in Algorithms

A curated reading list exploring how algorithmic bias can affect everything from health outcomes to financial credit to criminal justice.

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Algorithms and the data that drive them are designed and created by people, which means those systems can carry biases based on who builds them and how they’re ultimately deployed. Safiya Umoja Noble, author of Algorithms of Oppression: How Search Engines Reinforce Racism, offers a curated reading list exploring how technology can replicate and reinforce racist and sexist beliefs, how that bias can affect everything from health outcomes to financial credit to criminal justice, and why data discrimination is a major 21st century challenge.

Google Has a Striking History of Bias Against Black Girls

Safiya Umoja Noble
Time

My first encounter with racism in search was in 2009 when I was talking to a friend who causally mentioned one day, “You should see what happens when you Google ‘black girls.’” I did and was stunned. (An excerpt from Algorithms of Oppression.)

Machine Bias

Julia AngwinJeff LarsonSurya MattuLauren Kirchner
ProPublica

There’s software used across the country to predict future criminals. And it’s biased against blacks.

Safiya Umoja Noble

Safiya Umoja Noble is an Associate Professor at the University of California, Los Angeles (UCLA) in the Department of Information Studies, where she serves as the Co-Director of the UCLA Center for Critical Internet Inquiry. She is the author of a best-selling book on racist and sexist algorithmic bias in commercial search engines, Algorithms of Oppression: How Search Engines Reinforce Racism (NYU Press).