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The convergence of virtual reality and social networks: threats to privacy and autonomy

Ó Brolcháin, Fiachra ORCID: 0000-0001-5290-8772, Jacquemard, Tim, Monaghan, David ORCID: 0000-0002-5169-9902, O'Connor, Noel E. ORCID: 0000-0002-4033-9135, Novitzky, Peter and Gordijn, Bert (2016) The convergence of virtual reality and social networks: threats to privacy and autonomy. Science and Engineering Ethics, 22 (2). pp. 1-29. ISSN 1471-5546

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Abstract

The rapid evolution of information, communication and entertainment technologies will transform the lives of citizens and ultimately transform society. This paper focuses on ethical issues associated with the likely convergence of virtual realities (VR) and social networks (SNs), hereafter VRSNs. We examine a scenario in which a significant segment of the world’s population has a presence in a VRSN. Given the pace of technological development and the popularity of these new forms of social interaction, this scenario is plausible. However, it brings with it ethical problems. Two central ethical issues are addressed: those of privacy and those of autonomy. VRSNs pose threats to both privacy and autonomy. The threats to privacy can be broadly categorized as threats to informational privacy, threats to physical privacy, and threats to associational privacy. Each of these threats is further subdivided. The threats to autonomy can be broadly categorized as threats to freedom, to knowledge and to authenticity. Again, these three threats are divided into subcategories. Having categorized the main threats posed by VRSNs, a number of recommendations are provided so that policy-makers, developers, and users can make the best possible use of VRSNs.

Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:Ethics
Subjects:Computer Science > Machine learning
Computer Science > Artificial intelligence
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Publisher:Springer-Verlag
Official URL:http://link.springer.com/article/10.1007/s11948-014-9621-1
Copyright Information:© 2015 Springer The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:20397
Deposited On:06 Nov 2015 11:33 by David Monaghan . Last Modified 05 Oct 2022 14:12

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