Reordering the “World of Things”: The Sociotechnical Imaginary of RFID Tagging and New Geographies of Responsibility

Science and Engineering Ethics 25 (5):1425-1446 (2019)

Abstract
The aim of this study is to investigate radio frequency identification tagging as a form of sociotechnical experimentation and the kinds of sociotechnical futures at stake in this experimentation. For this purpose, a detailed analysis of a publicly available promotional video by a tag producer for the fashion industry, a sector widely using RFID tags, was analysed in detail. The results of the study indicated that the sociotechnical imaginary of RFID tagging gravitates around the core value of perfect sociotechnical efficiency. This demands a high degree of readiness to engage in standardization efforts, which performs a specific materialized understanding of ethics by other means. Furthermore, the analysis points to the importance of considering the spatiotemporal dimensions in which RFID tags work when reflecting on how this technology matters to society. Finally, the analysis shows a tacit effort to keep RFID technology and thus any questions of responsible innovation confined to the shop floor. However, given the spreading of the use of RFIDs, much wider-ranging considerations are called for.
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DOI 10.1007/s11948-018-0071-z
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References found in this work BETA

Sorting Things Out: Classification and Its Consequences.Geoffrey C. Bowker & Susan Leigh Star - 2001 - Journal of the History of Biology 34 (1):212-214.
RFID: The Next Serious Threat to Privacy. [REVIEW]Vance Lockton & Richard S. Rosenberg - 2005 - Ethics and Information Technology 7 (4):221-231.
Laboratizing and de-Laboratizing the World.Michael Guggenheim - 2012 - History of the Human Sciences 25 (1):99-118.

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RFID: The Next Serious Threat to Privacy. [REVIEW]Vance Lockton & Richard S. Rosenberg - 2005 - Ethics and Information Technology 7 (4):221-231.
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Opinion Exchange Convergence Support Using RFID Tags.Wataru Sunayama & Yoshifumi Shimizu - 2011 - Transactions of the Japanese Society for Artificial Intelligence 26 (5):527-535.

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