Critical Tools for Machine Learning or CritML* is a project that brings together critical intersectional feminist theory and machine learning systems design. The goal of the project is to provide ways to work with critical theoretical concepts that are rooted in intersectional feminist, anti-racist, post/de-colonial research and actualize them in machine learning (ML) systems design. The project is also explicitly grounded in new materialist theoretical perspective and understands machine learning systems and their design as sociotechnical processes.
CritML consists (so far) of a series of workshops that explore concepts of “situated knowledges/situating”, “figurations/figuring”, “diffraction” and “critical fabulation/speculation” and work with them as guiding principles in ML systems design. These workshops open pathways to designing more inclusive, contextualized and accountable ML systems, and reframe their design as a transdisciplinary, contextualized process.
CritML is a work-in-progress led by Goda Klumbytė, an interdisciplinary researcher at Participatory IT Design department at the University of Kassel, Germany. Previously Goda has collaborated for this project with Claude Draude from Kassel and Alex Taylor at the Centre for Human-Computer Interaction Design at City, University of London, UK.
This website provides a constantly evolving toolbox of materials and workshop descriptions, and other information about the project. See more in the toolbox and publications or get in touch!
* This website has minimal imagery and other visual details. The idea is to keep it basic and better accessible for readers with low vision, those who use screen readers, and those who prefer visually calmer information environments for various reasons.
