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Neural Network Nebulaе: 'Black Boxes' of Technologies and Object-Lessons from the Opacities of Algorithms
[journal article]

dc.contributor.authorKuznetsov, Andrey G.de
dc.date.accessioned2024-10-23T14:43:00Z
dc.date.available2024-10-23T14:43:00Z
dc.date.issued2020de
dc.identifier.issn2074-0492de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/97346
dc.description.abstractThe paper deals with the quandary of the neutrality and transparency of technologies. First, I show how this problem is connected with the image of the opening of 'black boxes' that is pivotal to much of science and technology studies. Second, methodological and socio-political dimensions of the 'black box' metaphor are discussed. Third, I analyze three typical solutions to the problem of the neutrality of technologies outside and inside constructivist technology studies. It is demonstrated that despite their apparent differences, these solutions are similar in their logic of conceptualizing technology as a neutral intermediary. Forth, I look for an alternative to this logic in the actor-network theory of Bruno Latour. Here technologies are conceived in terms of an eventful association of heterogeneous entities irreducible to its conditions of possibility. The construction of technologies is understood as mediation, or as a 'making-do' process where creators are surprised by their creations and vice versa. In Latour's actor-network, technologies are interpreted as opaque and non-neutral entities. Finally, I turn to some object-lessons from smart technologies powered by neural networks to demonstrate that these are empirical vindications of Latour's conception of technical mediation. Particular attention is paid to the opacity and (non)interpretability of machine learning algorithms.de
dc.languagerude
dc.subject.ddcSoziologie, Anthropologiede
dc.subject.ddcSociology & anthropologyen
dc.subject.othervalue neutrality of technologies; black boxes; neural networks; machine learning; self-driving cars; science & technology studies (STS)de
dc.titleТуманности нейросетей: "черные ящики" технологий и наглядные уроки непрозрачности алгоритмовde
dc.title.alternativeNeural Network Nebulaе: 'Black Boxes' of Technologies and Object-Lessons from the Opacities of Algorithmsde
dc.description.reviewbegutachtetde
dc.description.reviewrevieweden
dc.source.journalSociologija vlasti / Sociology of power
dc.source.volume32de
dc.publisher.countryRUSde
dc.source.issue2de
dc.subject.classozWissenschaftssoziologie, Wissenschaftsforschung, Technikforschung, Techniksoziologiede
dc.subject.classozSociology of Science, Sociology of Technology, Research on Science and Technologyen
dc.subject.thesozAkteur-Netzwerk-Theoriede
dc.subject.thesozactor-network-theoryen
dc.subject.thesozTechnologiede
dc.subject.thesoztechnologyen
dc.identifier.urnurn:nbn:de:0168-ssoar-97346-7
dc.rights.licenceCreative Commons - Namensnennung, Nicht kommerz., Keine Bearbeitung 4.0de
dc.rights.licenceCreative Commons - Attribution-Noncommercial-No Derivative Works 4.0en
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10085258
internal.identifier.thesoz10035297
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo157-182de
internal.identifier.classoz10220
internal.identifier.journal2720
internal.identifier.document32
internal.identifier.ddc301
dc.identifier.doihttps://doi.org/10.22394/2074-0492-2020-2-157-182de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence20
internal.identifier.pubstatus1
internal.identifier.review2
dc.subject.classhort10200de
internal.pdf.validfalse
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse


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