GeDIS Paper on Machine Learning From a Feminist Epistemological Perspective to be Presented at EASST Conference
The paper looks at the principles of knowledge production and legitimization through data-based algorithms in machine learning. It asks what kind of conceptual models of learning and knowledge are proposed, and how these models can be re-evaluated from the perspective of feminist epistemologies. The paper will be part of the panel ‘The power of correlation and the promises of auto-management. On the epistemological and societal dimension of data-based algorithms’, led by Jutta Weber (University of Paderborn) and Gabriele Gramelsberger.
Read more about the panel and the full conference.