Suchergebnisse

With the development of new technologies and their increased applications in the context of a local government, cities have started to claim that they are smart. Smart Cities make use of Information and Communication Technologies (ICTs) to support planning and policy making. For an appropriate and sustainable functioning of these smart cities, collecting data about the different aspects of their territory and operations, including its citizens, is a crucial activity. Currently, there are two main avenues in which smart cities can collect data about their citizens: either through sensors, and cameras strategically placed throughout the city or by asking citizens to voluntarily donate to the local government their personal data (i.e., citizen engagement or 'e-participation'). Despite the growth and increasing prevalence of the latter practice, little attention has been given to how individuals experience the risks of data donation. Often, studies consider data donation as an aspect of the phenomenon of surveillance, or as a type of data sharing. This study theorises and empirically examines data donation and its risks as a phenomenon which is separate from either surveillance or data sharing. Focusing on mobility data, this study draws on two established donation and privacy risk frameworks to investigate how the risks of donating personal data to a smart city are experienced and socially constructed. The thematic analysis of ten focus groups conducted showed that, in the context of this empirical examination, privacy-specific risks alone do not constitute constructed risks. Instead, they combine in various ways with perceived donation risks to constitute more nuanced and embedded risk constructions. Donation risks are seen as potential consequences of privacy risks and combined they constitute the risks of donating data. This thesis underlines the importance of the context under which data donation takes place as well as privacy's value in a free and democratic society. ; "This work was supported by the University of St Andrews and the Social Sciences and Humanities Research Council of Canada (SSHRC) under the 'Big Data Surveillance' partnership grant. The grant's reference is: SSHRC 895-2015-1003" -- Funding