What question did this study set out to answer?

The aim is to develop a Feminist AI Framework that addresses both biases in technology and the structural causes behind them.

June 10, 2026Open Access

Beyond inclusion: feminist AI for transformative justice in STEM

Key Points

The aim is to develop a Feminist AI Framework that addresses both biases in technology and the structural causes behind them.
Extensive classroom exercises using text-to-image generators
Application of feminist STS and intersectionality concepts in AI development
Integration of feminist analysis into technical literacy programs
Advocation for incorporating feminist perspectives in AI deployment and STEM education
Highlighting the limitations of existing human-centred AI in addressing structural issues
Emphasizing the need for a comprehensive approach to tackle algorithmic harms

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.

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Cite This Study

Tanja Kubes (Thu,) studied this question.

synapsesocial.com/papers/6a28ff336f82f25be989c318 https://doi.org/https://doi.org/10.17169/refubium-52366

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