Abstract While human-centred AI (HCAI) has emerged as a commonly deployed response to algorithmic harms, it remains largely reactive and limited in addressing their structural causes. Drawing on feminist STS, intersectionality, critical posthumanism, and more-than-human anthropology, the paper proposes a more comprehensive Feminist AI Framework (FAIF) that expands existing approaches by addressing both immediate biases and the onto-epistemological assumptions sustaining them and positions feminist analysis as integral to technical literacy. Drawing on extensive classroom exercises using text-to-image generators, the paper argues for the systematic integration of feminist perspectives into the development and deployment of AI and in STEM education in general.
Tanja Kubes (Wed,) studied this question.
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