Data Feminism

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This work presents a transformative perspective on data science and ethics through the lens of intersectional feminism. Data science wields significant power, capable of both addressing injustices and perpetuating discrimination. This duality prompts critical questions: Who is conducting data science? For whom is it being done? Whose interests are prioritized? The prevailing narratives surrounding big data often reflect a white, male, and techno-heroic bias. The authors introduce a framework that challenges these norms, highlighting how questioning the male/female binary can disrupt other flawed hierarchical classifications. They illustrate how emotional understanding can enhance data visualization and how recognizing invisible labor reveals the human effort behind automated systems. Importantly, they assert that data does not inherently "speak for itself." This work provides actionable strategies for data scientists to incorporate feminist principles in their pursuit of justice, while also inviting feminists to engage with the expanding realm of data science. Ultimately, it transcends gender issues, focusing on power dynamics—who holds power, who does not, and how these imbalances can be addressed and transformed.