Sammanfattning
Self-tracking, defined as the utilisation of computational devices that track personal data about physiologies and everyday behaviours in the quest for self-knowledge, has become a vibrant area of interdisciplinary research. Ethnographic studies highlight how self-tracking devices shape self-experience, as they accentuate and amplify aspects of the self and daily comportment. Following the contextual uses of digital data and data analytics carefully casts doubt on universal claims about technologised futures. Studies benefit from a loosening of methodological and theoretical commitments in order to explore self-tracking as ‘an unknown’, rather than a pre-defined research object. One of the strengths of the anthropology of technology is its multi-stability, a quality that facilitates the exploration of the phenomenon under study from contradictory and complementary perspectives. Self-tracking research maintains its originality if it finds ways to engage with the different registers and scales that are at play in processes of datafication and everyday techno-engagements. Ultimately, self-tracking-related research deals with the long-standing question: What and how is human? Technologies shape assumptions and promises of life, connecting anthropological research to the way in which specific devices and algorithmic systems are part of the processes in which the human is extended, reduced, inspired, and overpowered.
Originalspråk | engelska |
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Titel på värdpublikation | The Palgrave Handbook of the Anthropology of Technology |
Redaktörer | M.H. Bruun et al. |
Antal sidor | 19 |
Förlag | Springer Nature |
Utgivningsdatum | mars 2022 |
Sidor | 253-271 |
ISBN (tryckt) | 978-981-16-7083-1 |
ISBN (elektroniskt) | 978-981-16-7084-8 |
DOI | |
Status | Publicerad - mars 2022 |
MoE-publikationstyp | A3 Del av bok eller annan forskningsbok |
Bibliografisk information
Publisher Copyright:© The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2022.
Vetenskapsgrenar
- 113 Data- och informationsvetenskap