Journal article
Privacy, technology, and norms: The case of Smart Meters
Social science research, Vol.51, pp.64-76
05/2015
Handle:
https://hdl.handle.net/2376/108548
PMID: 25769852
Abstract
•Technology associated privacy threats increase anti-technology norms.•Selling of data and ability to intervene in the home create the strongest anti-technology norms.•Effects of privacy threats do not vary with age.
Norms shift and emerge in response to technological innovation. One such innovation is Smart Meters – components of Smart Grid energy systems capable of minute-to-minute transmission of consumer electricity use information. We integrate theory from sociological research on social norms and privacy to examine how privacy threats affect the demand for and expectations of norms that emerge in response to new technologies, using Smart Meters as a test case. Results from three vignette experiments suggest that increased threats to privacy created by Smart Meters are likely to provoke strong demand for and expectations of norms opposing the technology and that the strength of these normative rules is at least partly conditional on the context. Privacy concerns vary little with actors’ demographic characteristics. These findings contribute to theoretical understanding of norm emergence and have practical implications for implementing privacy protections that effectively address concerns of electricity users.
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Details
- Title
- Privacy, technology, and norms: The case of Smart Meters
- Creators
- Christine Horne - Department of Sociology, Washington State University, United StatesBrice Darras - Department of Sociology, Washington State University, United StatesElyse Bean - Department of Sociology, Washington State University, United StatesAnurag Srivastava - School of Electrical Engineering and Computer Science, Washington State University, United StatesScott Frickel - Department of Sociology, Brown University, United States
- Publication Details
- Social science research, Vol.51, pp.64-76
- Academic Unit
- Sociology, Department of; Electrical Engineering and Computer Science, School of
- Publisher
- Elsevier Inc
- Identifiers
- 99900547146801842
- Language
- English
- Resource Type
- Journal article