Media coverage of violence against women often reinforces patriarchal norms—e.g., victim-blaming, excusing the perpetrator, or failing to situate the case as part of a larger system issue—and contributes to public inaction, state negligence, and a broader “pedagogy of cruelty.” This project will address patriarchal media narratives around gender-related violence and feminicide through the co-production of datasets and artificial intelligence (AI) tools that can support identifying and shifting harmful reporting. Specifically, we will co-create a taxonomy of harmful and constructive reporting practices with feminist activists and journalists across diverse cultural contexts. We will host a series of collaborative, multilingual workshops to produce this taxonomy and annotate examples. In doing so, we will explore participatory data workshops as a site for capacity-building, knowledge-sharing, and collective care and joy, reimagining alternatives to traditional, extractive data practices. The production of this dataset will form the basis for the future co-design of AI tools to identify harmful practices and/or suggest alternative helpful practices. This project will contribute to multiple, interdisciplinary academic communities, including media and journalism scholars who study public discourse and narratives around gender-related violence, and data science or AI researchers who aim to design community-centered, participatory approaches to data work.

Faculty project director: Dr. Harini Suresh, Assistant Professor Computer Science,
Brown University
Additional cross-disciplinary faculty director: Catherine D’Ignazio, Associate
Professor of Urban Studies and Planning, MIT
Project team members:
Dr. Helena Suárez Val, Feminicidio Uruguay
Dr. Isadora Cruxên, Lecturer in Business and Society, Queen Mary University of London
Dr. Alessandra Jungs de Almeida, Postdoctoral Associate in Women and Gender
Studies, MIT
Yujia Gao, PhD Student in Computer Science, Brown University