Participatory Machine Learning Models in Feminicide News Alert Detection

Abstract

After criminal recidivism or hiring machine learning mod-els have inflicted harm, participatory machine learning meth-ods are often used as a corrective positioning. However, lit-tle guidance exists on how to develop participatory machinelearning models throughout stages of the machine learningdevelopment life-cycle. Here we demonstrate how to co-design and partner with community groups, in the specificcase of feminicide data activism. We co-designed and piloteda machine learning model for the detection of media arti-cles about feminicide. This provides a feminist perspectiveon practicing participatory methods in a co-creation mind-set for the real-world scenario of monitoring violence againstwomen.