This workshop draws on feminist and other critical methodologies to construct interdisciplinary interventions in the design of machine learning systems. Theoretical concepts of “figuration”,
“situating/situated knowledge”, “critical fabulation/speculation,” and “diffraction”
are explored through hands-on experimentation to imagine and design machine learning
systems in a more situated, inclusive, contextualize and accountable way. Through
this “theory turned practice” approach the workshop aims to address systemic socio-cultural
biases and develop more socially responsible frameworks of design. The workshop provides
space for building a network for future research on interdisciplinary machine learning
systems design.
%0 Conference Paper
%1 10.1145/3464385.3467475
%A Klumbyte, Goda
%A Draude, Claude
%A Taylor, Alex
%B CHItaly 2021: 14th Biannual Conference of the Italian SIGCHI Chapter
%C New York, NY, USA
%D 2021
%I Association for Computing Machinery
%K gedispub gender innovation itegpub myown
%R 10.1145/3464385.3467475
%T Critical Tools for Machine Learning: Situating, Figuring, Diffracting, Fabulating Machine Learning Systems Design
%U https://doi.org/10.1145/3464385.3467475
%X This workshop draws on feminist and other critical methodologies to construct interdisciplinary interventions in the design of machine learning systems. Theoretical concepts of “figuration”,
“situating/situated knowledge”, “critical fabulation/speculation,” and “diffraction”
are explored through hands-on experimentation to imagine and design machine learning
systems in a more situated, inclusive, contextualize and accountable way. Through
this “theory turned practice” approach the workshop aims to address systemic socio-cultural
biases and develop more socially responsible frameworks of design. The workshop provides
space for building a network for future research on interdisciplinary machine learning
systems design.
%@ 9781450389778
@inproceedings{10.1145/3464385.3467475,
abstract = { This workshop draws on feminist and other critical methodologies to construct interdisciplinary interventions in the design of machine learning systems. Theoretical concepts of “figuration”,
“situating/situated knowledge”, “critical fabulation/speculation,” and “diffraction”
are explored through hands-on experimentation to imagine and design machine learning
systems in a more situated, inclusive, contextualize and accountable way. Through
this “theory turned practice” approach the workshop aims to address systemic socio-cultural
biases and develop more socially responsible frameworks of design. The workshop provides
space for building a network for future research on interdisciplinary machine learning
systems design.},
added-at = {2021-08-04T11:31:06.000+0200},
address = {New York, NY, USA},
articleno = {39},
author = {Klumbyte, Goda and Draude, Claude and Taylor, Alex},
biburl = {https://www.bibsonomy.org/bibtex/28df822d12b742acde0b740c4fcac1d34/godaklumbyte},
booktitle = {CHItaly 2021: 14th Biannual Conference of the Italian SIGCHI Chapter},
doi = {10.1145/3464385.3467475},
interhash = {45f08a66275dc30f3b37d8e6e350c00f},
intrahash = {8df822d12b742acde0b740c4fcac1d34},
isbn = {9781450389778},
keywords = {gedispub gender innovation itegpub myown},
location = {Bolzano, Italy},
numpages = {2},
publisher = {Association for Computing Machinery},
series = {CHItaly '21},
timestamp = {2021-08-04T11:34:05.000+0200},
title = {Critical Tools for Machine Learning: Situating, Figuring, Diffracting, Fabulating Machine Learning Systems Design},
url = {https://doi.org/10.1145/3464385.3467475},
year = 2021
}