Big Data: Inequality by Design?

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dc.contributor.authorPrietl, Bianca
dc.date.accessioned2023-08-29T12:09:32Z
dc.date.available2023-08-29T12:09:32Z
dc.date.issued2019
dc.description.abstractThis paper proposes to tackle the problem of digital inequality by introducing digital technologies of knowledge generation and decision-making to a feminist critique of rationality that is informed by discourse theory and intersectional perspectives on gender and gendered relations of inequality. Therefore, it takes a closer look at the epistemological foundations of Big Data as one prominent representation of digital technologies. While Big Data and Big Data-based results and decisions are generally believed to be objective and neutral, numeral cases of algorithmic discrimination have lately begged to differ. This paper argues that algorithmic discrimination is neither random nor accidental; on the contrary, it is - amongst others - the result of the epistemological foundation of Big Data - namely: data fundamentalism, post-explanatory anticipatory pragmatics, and anti-political solutionism. As a consequence, a critical engagement with the concepts and premises that become materialized in the design of digital technologies is needed, if they are not to silently (re)produce social inequalities.en
dc.description.sponsorshipThis work has been funded by the Federal Ministry of Education and Research of Germany (BMBF) (grant no.: 16DII111, 16DII112, 16DII113, 16DII114, 16DII115, 16DII116, 16DII117 – „Deutsches Internet-Institut“)
dc.identifier.citationPrietl, B. (2019). Big Data: Inequality by Design? Proceedings of the Weizenbaum Conference 2019: Challenges of Digital Inequality, 75–84. https://doi.org/10.34669/WI.CP/2.11
dc.identifier.doihttps://doi.org/10.34669/wi.cp/2.11
dc.identifier.eissn2510-7666
dc.identifier.urihttps://www.weizenbaum-library.de/handle/id/115
dc.language.isoeng
dc.publisherWeizenbaum Institute
dc.relation.ispartofhttps://doi.org/10.34669/WI.CP/2.32
dc.relation.ispartofseriesWeizenbaum Conference Proceedings
dc.rightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectTechnology (Applied sciences)en
dc.subjectTechnology Assessmenten
dc.subjectdiscourse theoryen
dc.subjectintersectionalityen
dc.subjectalgorithmen
dc.subjectdigitalizationen
dc.subjectepistemologyen
dc.subjectFoucault, Michelen
dc.subjectsocial inequalityen
dc.subjectdigital divideen
dc.subjectgender-specific factorsen
dc.subjecttechnology assessmenten
dc.subjectTechnik, Technologiede
dc.subjectBig Datade
dc.subjectTechnikfolgenabschätzungde
dc.subjectErkenntnistheoriede
dc.subjectIntersektionalitätde
dc.subjectDigitale Spaltungde
dc.subjectDigitalisierungde
dc.subjectAlgorithmusde
dc.subjectFoucault, Michelde
dc.subjectsoziale Ungleichheitde
dc.subjectDiskurstheoriede
dc.subject.ddc600 Technik
dc.subject.ddc004 Informatik
dc.subject.ddc300 Sozialwissenschaften
dc.titleBig Data: Inequality by Design?
dc.typeConferencePaper
dc.type.statuspublishedVersion
dcmi.typeText
dcterms.bibliographicCitation.booktitleProceedings of the Weizenbaum Conference 2019
dcterms.bibliographicCitation.originalpublisherplaceBerlin
dcterms.bibliographicCitation.pageend84
dcterms.bibliographicCitation.pagestart75
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Proceedings of the Weizenbaum Conference 2019: Challenges of Digital Inequality