What is Data Feminism?

Sexism, racism and other forms of discrimination are emerging within data products

• “Data is never a raw, truthful input – and it is never neutral”, this is the belief of Catherine D’Ignazio, co-author of the book Data Feminism.
• Data feminism is a framework for thinking about data science and ethics that is guided by ideas of intersectional feminism.
• Intersectional feminism follows the belief that race, class, sexuality, ability, age, religion, and more, are all factors that influence individual experience, opportunity and privilege.
• Data feminism applies the belief that as data is created by humans, it is open to human bias and as a result it cannot be neutral. Therefore, when interpreting data this should be kept in mind.
• Catherine D’Ignazio and Lauren Klein argue that firstly those working with data science must attune themselves to the ways in which oppressive forces can insert themselves into a data pipeline.
• Secondly, they state that once data scientists are aware of such oppressions, they can then utilise the data and computation to tackle inequality in the field.