Feminist epistemology for machine learning systems design

Autor:	Klumbyte, Goda, Piehl, Hannah, Draude, Claude
Rok vydání:	2023
Předmět:	Computer Science - Computers and Society Computer Science - Human-Computer Interaction K.4.0 K.4.3 H.1.2 H.5.2 H.5.3
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:	http://arxiv.org/abs/2310.13721 Zobrazit plný text záznamu View this record from Arxiv