Media Mentions: Jurafsky

Dan Jurafsky's work on measuring gender and ethnic stereotypes was featured earlier this week in a Stanford News Service article, "Stanford researchers use machine-learning algorithm to measure changes in gender, ethnic bias in U.S." The article featured the very recently published PNAS article "Word embeddings quantify 100 years of gender and ethnic stereotypes", co-authored by Nikhil Garg, Londa Schiebinger, Dan Jurafsky, and James Zou, which discusses how the Stanford-based interdisciplinary team analyzed word embeddings for over a century's worth of text data.