What is Data Feminism?

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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.
Articles from 4 publishers

4 articles on this topic


Catherine D’Ignazio: 'Data is never a raw, truthful input – and it is never neutral'

1 min read

None Of Us Are Free If Some Of Us Are Not: Catherine D’Ignazio on Data Feminism

13 min read
IEEE Spectrum

Can Feminist Robots Challenge Our Biases?

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8 min read

Intersectionality, Inequity And Imminence Of AI:

10 min read