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 […]
Tag: machine learning
Call for Participation: Critical Tools for Machine Learning
Join a workshop “Critical Tools for Machine Learning” as part of CHItaly conference on July 11, 2021.
Experimenting with flows of work: how to create modes of working towards epistemic justice?
This is part three of a blog post series reflecting on a workshop, held at FAccT conference 2020 in Barcelona, about machine learning and epistemic justice. If you are interested in the workshop concept and the theory behind it as well as what is a […]
“Where is the difficulty in that?” On planning responsible interdisciplinary collaboration
By Aviva de Groot, Danny Lämmerhirt, Phillip Lücking, Goda Klumbyte, Evelyn Wan This is the first in a series of blog posts on experiences gathered during the planning, execution and reflection of our workshop “Lost in Translation: An Interactive Workshop Mapping Interdisciplinary Translations for Epistemic […]
Lost in translation? Invitation to address the challenges of interdisciplinary cooperation in the FAT community
This post was originally published on Medium on 11 December 2019 and was written by Aviva de Groot, Danny Lämmerhirt, Evelyn Wan, Goda Klumbyte, Mara Paun, Phillip Lücking, and Shazade Jameson Introduction: The short of it The rapid deployment of complex computational, data-intense infrastructures profoundly […]