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Using algorithms to measure changes in gender, ethnic bias in U.S.

A Stanford team used special algorithms to detect the evolution of gender and ethnic biases among Americans from 1900 to the present. (Image credit: mousitj / Getty Images)

Apr 3 2018

Posted In:

Faculty, In the News

Aritcle written by Alex Shashkevich

"Artificial intelligence systems and machine-learning algorithms have come under fire recently because they can pick up and reinforce existing biases in our society, depending on what data they are programmed with.  A Stanford team used special algorithms to detect the evolution of gender and ethnic biases among Americans from 1900 to the present.

But an interdisciplinary group of Stanford scholars,  including STS Affiliated Faculty, Londa Schiebinger, turned this problem on its head in a new Proceedings of the National Academy of Sciences paper published April 3."