Tracking a critical look at the critical turn in data science: From “data feminism” to transnational feminist data science

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6 Scopus citations

Abstract

Through a critical analysis of recent developments in the theory and practice of data science, including nascent feminist approaches to data collection and analysis, this commentary aims to signal the need for a transnational feminist orientation towards data science. I argue that while much needed in the context of persistent algorithmic oppression, a Western feminist lens limits the scope of problems, and thus—solutions, critical data scholars, and scientists can consider. A resolutely transnational feminist approach on the other hand, can provide data theorists and practitioners with the hermeneutic tools necessary to identify and disrupt instances of injustice in a more inclusive and comprehensive manner. A transnational feminist orientation to data science can pay particular attention to the communities rendered most vulnerable by algorithmic oppression, such as women of color and populations in non-Western countries. I present five ways in which transnational feminism can be leveraged as an intervention into the current data science canon.

Original languageEnglish (US)
JournalBig Data and Society
Volume9
Issue number2
DOIs
StatePublished - Jul 2022

Keywords

  • Data
  • critical algorithm studies
  • critical data studies
  • feminism
  • postcolonial studies
  • transnational feminism

ASJC Scopus subject areas

  • Information Systems
  • Communication
  • Computer Science Applications
  • Information Systems and Management
  • Library and Information Sciences

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