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Anticipating education: governing habits, memories and policy-futures
- Source :
- Learning, Media and Technology. 45:284-297
- Publication Year :
- 2019
- Publisher :
- Informa UK Limited, 2019.
-
Abstract
- The use of data to govern education is increasingly supported by the use of knowledge-based technologies, including algorithms, artificial intelligence (AI), and tracking technologies [Fenwick, T., E. Mangez, and J. Ozga. 2014. Governing Knowledge: Comparison, Knowledge-Based Technologies and Expertise in the Regulation of Education. New York, NY: Routledge]. New forms of datafication and automation enable governments and other powerful stakeholders to draw from the past to construct images of educational futures in order to steer the present. This paper examines the competing conceptions of time and temporality that AI posits for policy and practice when used to anticipate educational futures. We argue that most educational futures are already delineated, and machinic expressions of time are the chronologies, habits, and memories that the educated subject inhabits rather than produces. If resetting educational habits and memories can be an alternative to algorithmic anticipations of education then we believe, paradoxically, that machines may help to reset them by accelerating them. Refereed/Peer-reviewed
- Subjects :
- education policy
Knowledge management
business.industry
Knowledge economy
Corporate governance
05 social sciences
050301 education
050801 communication & media studies
Temporality
artificial intelligence
Anticipatory governance
Education
0508 media and communications
Media Technology
Sociology
Tracking (education)
Education policy
business
0503 education
Futures contract
anticipatory governance
time
temporality
Subjects
Details
- ISSN :
- 17439892 and 17439884
- Volume :
- 45
- Database :
- OpenAIRE
- Journal :
- Learning, Media and Technology
- Accession number :
- edsair.doi.dedup.....cdc32340ec802a2dd1f4686f5255ca9a