Difference between revisions of "Adrian Mackenzie"
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* ''[http://monoskop.org/log/?p=382 Cutting Code: Software and Sociality]'', New York: Peter Lang, 2006. | * ''[http://monoskop.org/log/?p=382 Cutting Code: Software and Sociality]'', New York: Peter Lang, 2006. | ||
* ''[http://monoskop.org/log/?p=3119 Wirelessness: Radical Empiricism in Network Cultures]'', MIT Press, 2010. | * ''[http://monoskop.org/log/?p=3119 Wirelessness: Radical Empiricism in Network Cultures]'', MIT Press, 2010. | ||
| + | * ''Machine Learners: Archaeology of a Data Practice'', MIT Press, 2017, 272 pp. [https://mitpress.mit.edu/books/machine-learners] | ||
; Links | ; Links | ||
* [http://www.lancaster.ac.uk/fass/sociology/profiles/adrian-mackenzie Profile at U Lancaster] | * [http://www.lancaster.ac.uk/fass/sociology/profiles/adrian-mackenzie Profile at U Lancaster] | ||
* [https://twitter.com/rian2011ad Twitter] | * [https://twitter.com/rian2011ad Twitter] | ||
| + | * [http://aaaaarg.fail/maker/5310647b334fe071e0b90835 ARG] | ||
[[Category:Writers]] [[Category:Software studies]] {{DEFAULTSORT:Mackenzie, Adrian}} | [[Category:Writers]] [[Category:Software studies]] {{DEFAULTSORT:Mackenzie, Adrian}} | ||
Revision as of 10:11, 4 April 2018
Adrian Mackenzie (Professor in Technological Cultures, Sociology Department, Lancaster University) researches in the area of technology, science and culture. He is currently working on the circulation of data intensive methods across science, government, and business in network media, exploring how number, quality, space and feeling are re-configured through predictions and anticipations of change (Into the Data: An Archaeology of Machine Learning, MIT Press, 2017). He co-directs the Centre for Science Studies, Lancaster University.
- Monographs
- Transductions: Bodies and Machines at Speed, Technologies, Studies in Culture & Theory, London: Continuum, 2002.
- Cutting Code: Software and Sociality, New York: Peter Lang, 2006.
- Wirelessness: Radical Empiricism in Network Cultures, MIT Press, 2010.
- Machine Learners: Archaeology of a Data Practice, MIT Press, 2017, 272 pp. [1]
- Links
