Savic, Selena

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Savic
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Selena
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Savic, Selena

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2022 - 20232
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Item-Typ: Publikation × Typ: 01A - Beitrag in wissenschaftlicher Zeitschrift × Thema: 700 - Künste und Unterhaltung ×

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Gerade angezeigt 1 - 2 von 2
  • Vorschaubild
    Publikation
    Making Arguments with Data: Resisting Appropriation and Assumption of Access / Reason in Machine Learning Training Processes
    (Weizenbaum Institute for the Networked Society, 30.10.2023) Savic, Selena; Martins, Yann Patrick [in: Weizenbaum Journal of the Digital Society]
    This 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.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Articulating nomadic identities of radio signals
    (Revistes científiques de la Universitat de Barcelona, 25.02.2022) Savic, Selena [in: Matter: Journal of New Materialist Research]
    This article presents a new materialist approach to artificial neural networks, based on experimental research in categorization of data on radio signals. Picking up on Rossi Braidotti’s nomadic theory and a number of new materialist perspectives on informatics, the article presents identification of radio signals as a process of articulating identities with data: nomadic identities that are informed by all the others, always established anew. As a resistance to the dominant understanding of data as discreet, the experiments discussed here demonstrate a way to work with a digital archive in a materialist and non-essentialist way. The output of experiments, data observatories, shows the capacity of machine learning techniques to challenge fixed dichotomies, such as human/nature, and their role in the way we think of identities. A data observatory is a navigation apparatus which can be used to orient oneself in the vast landscape of data on radio transmissions based on computable similarity. Nomadic identities render materiality of radio signals as digital information.
    01A - Beitrag in wissenschaftlicher Zeitschrift