Human/machine Learning: Becoming Responsible for Learning Cultures of Digital Technologies
Autor: | Treusch, Pat |
---|---|
Rok vydání: | 2019 |
Předmět: |
Sociology & anthropology
Soziologie Anthropologie Digital Human-Machine Relations Feminist STS Weizenbaum-Institut Weizenbaum Institute Wissenschaftssoziologie Wissenschaftsforschung Technikforschung Techniksoziologie Sociology of Science Sociology of Technology Research on Science and Technology learning digitalization man-machine system learning culture technological progress feminism technischer Fortschritt Feminismus Lernen Lernkultur Digitalisierung Mensch-Maschine-System 20200 |
Zdroj: | Proceedings of the Weizenbaum Conference 2019 "Challenges of Digital Inequality - Digital Education, Digital Work, Digital Life", 8, Weizenbaum Conference, 2 |
Druh dokumentu: | Konferenzbeitrag<br />conference paper |
DOI: | 10.34669/wi.cp/2.22 |
Popis: | This paper centrally asks for the ways in which ubiquitous, ever new digital technologies of 'our' everyday lives transform learning at the digital human-machine interface from the perspective of feminist science and technology studies. How to account for emerging forms of interwoven human and machine learning? Suggesting the term of learning cultures in approaching this question, the paper emphasizes an understanding of learning not as a proficiency of an entity embodying either natural or artificial intelligence, but rather as a culturally situated and materially enacted process. In so doing, the paper brings together recent impulses that suggest a re-conceptualization of learning, e.g. through the notion of "machine learners" (Mackenzie 2017) or that of "posthuman learning (Hasse 2018)". Reading these insights together, I will finally suggest an account of becoming responsible for learning cultures of digital technologies through a reconsidered notion of interwoven human/machine learning. |
Databáze: | SSOAR – Social Science Open Access Repository |
Externí odkaz: |