Making Arguments with Data: Resisting Appropriation and Assumption of Access / Reason in Machine Learning Training Processes

dc.contributor.authorSavic, Selena
dc.contributor.authorMartins, Yann Patrick
dc.date.accessioned2023-11-09T07:47:06Z
dc.date.available2023-11-09T07:47:06Z
dc.date.issued2023-10-30
dc.description.abstractThis article presents an approach to practicing ethics when working with large datasets and designing data representations. Inspired by feminist critique of technoscience and recent problematizations of digital literacy, we argue that machine learning models can be navigated in a multi-narrative manner when access to training data is well articulated and understood. We programmed and used web-based interfaces to sort, organize, and explore a community-run digital archive of radio signals. An additional perspective on the question of working with datasets is offered from the experience of teaching image synthesis with freely accessible online tools. We hold that the main challenge to social transformations related to digital technologies comes from lingering forms of colonialism and extractive relationships that easily move in and out of the digital domain. To counter both the unfounded narratives of techno-optimismand the universalizing critique of technology, we discuss an approachto data and networks that enables a situated critique of datafication and correlationism from within.
dc.identifier.doihttps://doi.org/10.34669/WI.WJDS/3.2.4
dc.identifier.issn2748-5625
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/38381
dc.identifier.urihttps://doi.org/10.26041/fhnw-5663
dc.issue2
dc.language.isoen
dc.publisherWeizenbaum Institute for the Networked Society
dc.relationMaking Arguments with Data, 2022-09-01
dc.relation.ispartofWeizenbaum Journal of the Digital Society
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.spatialBerlin
dc.subjectethics of digital tools
dc.subjectcritical data studies
dc.subjectdata observatories
dc.subjectassumption of access
dc.subjectsituated knowledge
dc.subjectmachine learning
dc.subjectartificial intelligence
dc.subject.ddc700 - Künste und Unterhaltung
dc.titleMaking Arguments with Data: Resisting Appropriation and Assumption of Access / Reason in Machine Learning Training Processes
dc.type01A - Beitrag in wissenschaftlicher Zeitschrift
dc.volume3
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.ReviewTypeAnonymous ex ante peer review of a complete publication
fhnw.affiliation.hochschuleHochschule für Gestaltung und Kunstde_CH
fhnw.affiliation.institutInstitut Experimentelles Design und Medienkulturende_CH
fhnw.openAccessCategoryDiamond
fhnw.publicationStatePublished
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relation.isAuthorOfPublication541e1800-63d5-4bdd-9bdc-e888d47e7b70
relation.isAuthorOfPublication.latestForDiscovery7b9e7a0f-7a23-4d42-837c-3279961feea7
relation.isProjectOfPublicationd3aba820-5754-4119-b2e3-0301b5736826
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