Feminist Ai Critical Perspectives On Algorithms Data And Intelligent Machines Jude Browne by Jude Browne, Stephen Cave, Eleanor Drage, Kerry Mcinerney 9780192889898, 0192889893 instant download after payment.

Chapters 5, 12, and 18 of this work are available under the terms of a CC BY-NC-ND 4.0 International open access licence. These parts of the work are free to read on the Oxford Academic platform and offered as a free PDF download from OUP and selected open access locations.
Feminist AI: Critical Perspectives on Algorithms, Data and Intelligent Machines is the first volume to bring together leading feminist thinkers from across the disciplines to explore the impact of artificial intelligence (AI) and related data-driven technologies on human society.
Recent years have seen both an explosion in AI systems and a corresponding rise in important critical analyses of these technologies. Central to these analyses has been feminist scholarship, which calls upon the AI sector to be accountable for designing and deploying AI in ways that further, rather than undermine, the pursuit of social justice.
This book aims to be a touchstone text for AI researchers concerned with the social impact of their systems, as well as theorists, students and educators in the field of gender and technology. It demonstrates the importance of an intersectional understanding of the risks and benefits of AI, approaching feminism as a political project that aims to challenge various interlocking forms of injustice, social inequality and structural relations of power.
Feminist AI showcases the vital contributions of feminist scholarship to thinking about AI, data, and intelligent machines as well as laying the groundwork for future feminist scholarship on AI. It brings together scholars from a variety of disciplinary backgrounds, from computer science, software engineering, and medical sciences to political theory, anthropology, and literature. It provides an entry point for scholars of AI, science and technology into the diversity of feminist approaches to AI, and creates a rich dialogue between scholars and practitioners of AI to examine the powerful congruences and generative tensions between differen