Feminist epistemology for machine learning systems design
Autor: | Klumbyte, Goda, Piehl, Hannah, Draude, Claude |
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Rok vydání: | 2023 |
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Druh dokumentu: | Working Paper |
Popis: | This paper presents a series of feminist epistemological concepts as tools for developing critical, more accountable, and contextualised approaches to machine learning systems design. Namely, we suggest that the methods of situated knowledges or situating, figurations or figuring, diffraction or diffracting, and critical fabulation or speculation can be productively actualised in the field of machine learning systems design. We also suggest that the meta-method for doing this actualisation requires not so much translation but transposition - a creative and critical adaptation to speak to machine learning contexts. Comment: Workshop A Toolbox of Feminist Wonder - Theories and methods that can make a difference, Conference on Computer-Supported Cooperative Work and Social Computing CSCW 23, October 14-18, 2023, Minneapolis, MN, USA, 5 pages |
Databáze: | arXiv |
Externí odkaz: |