Towards Intersectional Feminist and Participatory ML - A Case Study in Supporting Feminicide Counterdata Collection

Explore a case study on intersectional feminist and participatory machine learning in a 15-minute conference talk presented at the Association for Computing Machinery (ACM). Delve into the critical issue of feminicide and the challenges of missing data. Learn about innovative approaches to data annotation, model development, and evaluation in the context of supporting feminicide counterdata collection. Gain insights from the results of stage 2 of the research project. Understand how this work contributes to the broader conversation on ethical and inclusive AI development, emphasizing the importance of intersectional feminist perspectives and participatory methods in addressing sensitive social issues through machine learning.

Intro
Motivation
Feminicide & Missing Data
Data Annotation
Model Development
Evaluation
Results: stage 2
Conclusion