An A.I. Training Tool Has Been Passing Its Bias to Algorithms for Almost Two Decades

Night after night, Fien de Meulder sat in front of her Linux computer flagging names of people, places, and organizations in sentences pulled from Reuters newswire articles. De Meulder and her colleague, Erik Tjong Kim Sang, worked in language technology at the University of Antwerp. It was 2003, and a 60-hour workweek was typical in academic circles. She chugged Coke to stay awake. The goal: develop an open source dataset to help machine learning (ML) models learn to identify and categorize entities in text.