Making Arguments with Data

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Logo des Projekt
DOI der Originalpublikation
Projekttyp
angewandte Forschung
Projektbeginn
01.09.2022
Projektende
31.08.2023
Projektstatus
abgeschlossen
Projektkontakt
Savic, Selena
Projektmanager:in
Beschreibung
Zusammenfassung
Whether we are discussing measures in order to ‘flatten the curve’ in a pandemic, or what to wear given the most recent weather forecast, we base arguments on patterns observed in data. With this teaching research project, we propose an approach to practicing ethics when working with large datasets and designing data representations. We use and continuously re-programme 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. We hold that the main challenge to digital ethics 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, this approach to data and networks enables a situated critique of datafication and correlationism from within.
Während FHNW Zugehörigkeit erstellt
Yes
Zukunftsfelder FHNW
Hochschule
Hochschule für Gestaltung und Kunst Basel FHNW
Institut
Experimentelles Design und Medien-Kulturen
Finanziert durch
Fachhochschule Nordwestschweiz FHNW, Lehrfonds
Projektpartner
Auftraggeberschaft
SAP Referenz
Schlagwörter
visual data study
situated knowledge
data observatories
machine learning
correlationism
critique from within
Fachgebiet (DDC)
Publikationen
Publikation
Making Arguments with Data
(09.06.2022) Savic, Selena; Martins, Yann Patrick
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.
06 - Präsentation
Vorschaubild
Publikation
Making Arguments with Data
(Weizenbaum Institute for the Networked Society - The German Internet Institute, 02/2023) Savic, Selena; Martins, Yann Patrick; Herlo. Bianca; Irrgang, Daniel
Whether we are discussing measures in order to "flatten the curve" in a pandemic or what to wear given the most recent weather forecast, we base arguments on patterns observed in data. This article presents an approach to practicing ethics when working with large datasets and designing data representations. We programmed and used web-based interfaces to sort, organize, and explore a community-run 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. 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 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.
04B - Beitrag Konferenzschrift
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
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

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