Feminist Machine Learning
Towards New Materialist Informatics
1st Edition
Will be published approx. on 30. November 2026
Book
Paperback/Softback
224 pages
978-1-5292-5685-7 (ISBN)
Description
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.
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.
More details
Series
Edition
First Edition
Language
English
Place of publication
Bristol
United Kingdom
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Illustrations
29 s/w Abbildungen
29 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
ISBN-13
978-1-5292-5685-7 (9781529256857)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Goda Klumbyte is Postdoctoral Researcher in Participatory IT Design at the University of Kassel and in Human-Computer Interaction at the University of Salzburg.
Content
1. Introduction: Feminist Machine Learning
2. Why Assemblage? Diagrammatics of Machine Learning
I. Algorithmic Agency: Probing the Epistemic Operations of Machine Learning
3. Linear Regression: From Regression to the Mean to Relation Machines
4. k-Nearest Neighbours: Homophily and the Making of Difference
5. Decision Trees: Arboreal Organization of Knowledge
6. Tying the Knots: Algorithms as Operational Diagrams
II. Learning Otherwise: Critical and Speculative Design Interventions
7. Diffracting Power: Critical Machine Learning Artefact Design
8. Activating Concepts: Redrawing Machine Learning Design Diagrams
9. Speculating Models, Inventing Algorithms: Experimental Diagrams
10. Towards New Materialist Informatics as a Critical Technical Practice
2. Why Assemblage? Diagrammatics of Machine Learning
I. Algorithmic Agency: Probing the Epistemic Operations of Machine Learning
3. Linear Regression: From Regression to the Mean to Relation Machines
4. k-Nearest Neighbours: Homophily and the Making of Difference
5. Decision Trees: Arboreal Organization of Knowledge
6. Tying the Knots: Algorithms as Operational Diagrams
II. Learning Otherwise: Critical and Speculative Design Interventions
7. Diffracting Power: Critical Machine Learning Artefact Design
8. Activating Concepts: Redrawing Machine Learning Design Diagrams
9. Speculating Models, Inventing Algorithms: Experimental Diagrams
10. Towards New Materialist Informatics as a Critical Technical Practice