DSpace

Whether we are discussing measures in order to ‘flatten the curve’ in the ongoing pandemic, or what to wear in face of the most recent weather forecast, we make arguments based on patterns and trends observed in data. What makes these patterns observable? Making arguments with data requires critical engagement with datasets, as well as computational processes to gather data, to organize and model their relationships. This article presents an approach to practicing ethics when working with large datasets and designing data representations. The arguments we make are based on the development and use of a computational instrument, and working with digital archives. We programmed and used web-based interfaces to sort, organize and explore a community-ran archive of radio signals. Inspired by feminist critique of technoscience and recent problematizations of digital literacy, we argue that one can navigate machine learning models in a multi-narrative manner, and that knowledge of radio signals or any other technical artefact transgresses domains. We propose visual explorations of complex data structures that enable storytelling and an understanding of datasets that resists extraction of discrete identities from the data. We hold that the main challenge to sovereignty comes from lingering forms of colonialism and extractive relationships that easily move in and out of the digital domain. Countering both the unbased narratives of techno-optimism, and the universalizing critique of technology, we discuss an approach to data and networks that enables a situated critique of datafication and correlationism from within.

Hochschule für Gestaltung und Kunst Basel FHNW

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Bereich: Suchergebnisse