Data Feminism Presents an Intersectional Feminist Way to Think About Data Science and Ethics

Author: Catherine D’Ignazio and Lauren Klein

Publisher: Ms. Magazine

Publication Year: 2020

Summary: The following article discusses how the dominant group of data scientists today are straight, white, cisgender man who has formal credentials and is from the United States. The world was designed for him and he may not think about how the world may treat others, who are not like him, differently. Due to limited knowledge, most people with good education and background can struggle with identifying existing problems in the world and coming up with solutions. This can make data science, a field dominated by these types of people, a racist and sexist place. For example, a Black graduate student, who was using facial analysis software could not detect her face. This is because Black females were only four percent of the faces used in the dataset.