After Explainability: Directions for Rethinking Current Debates on Ethics, Explainability, and Transparency 

EU guidelines on trustworthy AI posits that one of the key aspects of creating AI systems is accountability, the routes to which lead through, among other things, explainability and transparency of AI systems. While working on AI Forensics project, which positions accountability as a matter […]

Messy Concepts: How to Navigate the Field of XAI?

Entering the field of explainable artificial intelligence (XAI) entails encountering different terms that the field is based on. Numerous concepts are mentioned in articles, talks and conferences and it is crucial for researchers to familiarize themselves with them. To mention some, there’s explainability, interpretability, understandability, […]

critML: Critical Tools for Machine Learning that Bring Together Intersectional Feminist Scholarship and Systems Design

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 […]

Diffractive Readings: Cyberfeminism_ NewMaterialism_ Computing [video]

In September we – Goda, Loren and Claude – presented a paper at the Society for Social Studies of Science (4S) conference in New Orleans. We were (digitally) part of an amazing panel “Feminist Technoscience by Other Means: Reconfiguring Research Practices for World-Making Beyond the […]