Dis-positions: Troubling Methods and Theory in STS- Feminist Machine Learning

Available open access digitally under CC-BY-NC-ND licence. Machine learning shapes what we see, know and decide, yet the processes through which it operates often remain obscure. This bold and original book brings feminist theories of knowledge into direct dialogue with algorithmic systems design, revealing how machine learning systems encode power, difference and historical bias into their mathematical operations. Moving from critical analysis to creative intervention, it explores three widely used algorithms to show how design choices shape outcomes and embed social assumptions, before proposing radical new design strategies rooted in appropriation and experimentation. The result is a compelling call for a transdisciplinary critical technical practice - one that places feminist and new materialist thinking at the heart of how we build intelligent systems.

Pagina's: 224, Paperback, Bristol University Press