Projekter pr. år
Abstract
This paper provides a theoretical alternative to the prevailing perception of machine learning as synonymous with speed and efficiency. Inspired by ethnographic fieldwork and grounded in pragmatist philosophy, we introduce the concept of “data friction” as the situation when encounters between held beliefs and data patterns posses the potential to stimulate innovative thinking. Contrary to the conventional connotations of “speed” and “control,” we argue that computational methods can generate a productive dissonance, thereby fostering slower and more reflective practices within organizations. Drawing on a decade of experience in participatory data design and data sprints, we present a typology of data frictions and outline three ways in which algorithmic techniques within data science can be reimagined as “friction machines”. We illustrate these theoretical points through a dive into three case studies conducted with applied anthropologist in the movie industry, urban planning, and research.
Originalsprog | Engelsk |
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Tidsskrift | EPIC Proceedings |
Sider (fra-til) | 82-105 |
ISSN | 1559-8918 |
Status | Udgivet - 2023 |
Fingeraftryk
Dyk ned i forskningsemnerne om 'Friction by Machine: How to Slow Down Reasoning with Computational Methods'. Sammen danner de et unikt fingeraftryk.Projekter
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UB: The Urban Belonging Project
Burgos-Thorsen, S. (CoPI), Madsen, A. K. (PI (principal investigator)) & Ehn, D. E. H. (CoPI)
Gehl Architects, Innovationsfonden, Centre of Expertise for Creative Innovation, IT University of Copenhagen
01/02/2020 → 01/02/2023
Projekter: Projekt › Forskning
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How to make creatively accepted AI in the cultural industry?
Søltoft, J. I. & Munk, A. K., 9 jun. 2023.Publikation: Konferencebidrag uden forlag/tidsskrift › Konferenceabstrakt til konference › Forskning
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The Urban Belonging Photo App: A toolkit for studying place attachments with digital and participatory methods
Madsen, A. K., Burgos-Thorsen, S., De Gaetano, C., Ehn, D. E. H., Groen, M., Niederer, S., Norsk, K. & Simonsen, T., nov. 2023, I: Methodological Innovations. 16, 3, s. 292-314 23 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil5 Citationer (Scopus)150 Downloads (Pure) -
The Thick Machine: Anthropological AI Between Explanation and Explication
Munk, A. K., Knudsen, A. G. & Jacomy, M., 2022, I: Big Data & Society. 9, 1, s. 1-14 14 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil28 Citationer (Scopus)500 Downloads (Pure)