interdisciplinary voices in critical computing
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 […]
Based on their commitment to diversity, equity and inclusion in computing, the Association of Computing Machinery has put forward a list of considerations to forming diverse teams. This list includes inherent characteristics such as race and ethnicity, gender identity and disability, as well as acquired […]
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, […]
On January 29th and 30th 2024, a small but international group of scholars, civil society representatives, and practitioners came together at the Berlin Social Science Center to discuss the controversies, imaginaries, developments, and policy solutions surrounding AI under the name “Shifting AI Controversies – Prompts, […]
When thinking of computer science – what images pop into one’s head and what can those images tell us about the discipline as well as interconnected societal expectations and norms? In this short post we report on our research into gendered codings of computer science. […]
I have recently visited my first academic conference – the closing event of a project titled “Shaping AI” – and on the train journey back, after two days of presentations, soaking up knowledge, attempts at networking, and questions-turning-monologues, I left with one question: “Can this […]
November 9 & 10, 2023 09:00–12:30 BST / 10:00–13:30 CET / 04:00–07:30 ET / 20:00–23:30 AEDT Hybrid workshop (online + at Goldsmiths, London, UK) This workshop examines potential conceptual and practical correlations between Bayesian approaches, in statistics, data science, mathematics and other fields, and feminist […]
Explainable artificial intelligence (XAI) as a design perspective towards explainable AI can benefit from feminist perspectives. This post explores some dimensions of feminist approaches to explainability and human-centred explainable AI.
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 […]
The workshop series on “Methods, Theories, and Taking Action through Gender and Feminisms in Human Computer Interaction” was documented in a booklet.