Context and Participation in Machine Learning

Abstract

In AI & ML, participatory approaches hold promise to lend agency and decision-making power to marginalized stakeholders. But what does meaningful participation look like in practice? This talk will first cover an in-depth case study of designing ML tools with and in service of activists who monitor gender-related violence. Drawing from intersectional feminist theory and participatory design, we develop methods for data collection, annotation, modeling, and evaluation that aim to prioritize activist expertise and sustainable partnerships. Then, we’ll consider what participatory approaches should look like in the age of foundation models.