‘Depends on whos got the data’: Public understandings of personal digital dataveillance

by | May 8, 2017 | Research Publications

Author(s):

  • Lupton, Deborah
  • Michael, Mike

Abstract:

Post-Snowden, several highly-publicised events and scandals have drawn attention to the use of people’s personal data by other actors and agencies, both legally and illicitly. In this article, we report the findings of a project in which we used cultural probes to generate discussion about personal digital dataveillance. Our findings suggest the prevailing dominance of tacit assumptions about the uses and benefits of dataveillance as well as fears and anxieties about its possible misuse. Participants were able to identify a range of ways in which dataveillance is conducted, but were more aware of obvious commercial and some government actors. There was very little identification of the types of dataveillance that are used by national security and policing agencies or of illegal access by hackers and cybercriminals. We found that the participants recognised the value of both personal data and the big aggregated data sets that their own data may be part of, particularly for their own convenience. However, they expressed concern or suspicion about how these data may be used by others, often founded on a lack of knowledge about what happens to their data. The major question for our participants was where the line should be drawn. When does personal dataveillance become too intrusive, scary or creepy? What are its drawbacks and risks? Our findings suggest that experimenting with innovative approaches to elicit practices and understandings of personal digital data offers further possibilities for greater depth and breadth of social research with all types of social groups.

Document:

https://doi.org/10.24908/ss.v15i2.6332

References:
  1. Albrechtslund, Anders, and Peter Lauritsen. 2013. Spaces of everyday surveillance: Unfolding an analytical concept of participation.Geoforum49:310-316.doi: http://dx.doi.org/10.1016/j.geoforum.2013.04.016.
  2. Andrejevic, Mark. 2013. Infoglut: How Too Much Information is Changing the Way We Think and Know. New York: Routledge.
  3. Andrejevic, Mark. 2014. The big data divide.International Journal of Communication8:1673-1689.Andrejevic, Mark, and Mark Burdon. 2015. Defining the sensor society.Television & New Media16 (1):19-36.
  4. Boehner, Kirsten, William Gaver, and Andy Boucher. 2012. Probes.In Inventive Methods: The Happening of the Social, edited by Celia Lury and Nina Wakeford, 185-201. London: Routledge.
  5. Boehner, Kirsten, Janet Vertesi, Phoebe Sengers, and Paul Dourish. 2007. How HCI interprets the probes.Proceedings of CHI 2007, San Jose. ACM Press, 1077-1088.
  6. boyd, danah, and Kate Crawford. 2012. Critical questions for Big Data: provocations for a cultural, technological, and scholarly phenomenon.Information, Communication & Society15 (5):662-679.
  7. Crawford, Kate, and Jason Schultz. 2014. Big data and due process: toward a framework to redress predictive privacy harms.Boston College Law Review55 (1):93-128.
  8. Lupton and Michael: ‘Depends on Who’s Got the Data’Surveillance&Society 15(2)268Esposti, Sara Degli. 2014. When big data meets dataveillance: the hidden side of analytics.Surveillance & Society12 (2):209-225.
  9. Fuchs, Christian. 2011. Web 2.0,prosumption, and surveillance.Surveillance & Society8 (3):288-309.
  10. Gangadharan, Seeta Peña. 2015. The downside of digital inclusion: Expectations and experiences of privacy and surveillance among marginal Internet users.New Media & Society. DOI: 10.1177/1461444815614053.
  11. Gaver, William, Andrew Boucher, Sarah Pennington, and Brendan Walker. 2004. Cultural probes and the value of uncertainty. Interactions11(5):53-56.
  12. Kennedy, Helen, Dag Elgesem, and Cristina Miguel. 2015. On fairness: User perspectives on social media data mining.Convergenceonline first.DOI: 10.1177/1354856515592507.
  13. Klauser, Francisco R., and Anders Albrechtslund. 2014. From self-tracking to smart urban infrastructures: towards an interdisciplinary research agenda on Big Data.Surveillance & Society12 (2):273-286.
  14. Levy, Karen. 2015. Intimate surveillance. Idaho Law Review51:679-693.
  15. Lupton, Deborah. 2016a. Digital companion species and eating data: Implications for theorising digital data–human assemblages. Big Data & Society3 (1). Available at: http://bds.sagepub.com/spbds/3/1/2053951715619947.full.pdf. Accessed 7 January 2016.
  16. Lupton, Deborah. 2016b. The diverse domains of quantified selves: self-tracking modes and dataveillance.Economy and Society45(1):101-122.
  17. Lupton, Deborah. 2016c. The Quantified Self: A Sociology of Self-Tracking Cultures. Cambridge: Polity Press.Lyon, David, and Zygmunt Bauman. 2013. Liquid Surveillance: A Conversation. Oxford: Wiley.
  18. Madden, Mary. 2014. Public Perceptions of Privacy and Security in the post-Snowden Era. Pew Research Center.Madden, Mary, and Lee Rainie. 2015. Americans’ Attitudes about Privacy, Security and Surveillance. Pew Research Center.
  19. Mann, Steve, and Joseph Ferenbok. 2013. New media and the power politics of sousveillance in a surveillance-dominated world.Surveillance & Society11 (1/2):18-34.
  20. Marwick, Alice. 2012. The public domain: social surveillance in everyday life.Surveillance & Society9 (4):378-393.
  21. Michael, Mike, and Deborah Lupton. 2016. Toward a manifesto for the ‘public understanding of big data’.Public Understanding of Science25 (1):104-116.
  22. Nafus, Dawn. 2014. Stuck data, dead data, and disloyal data: the stops and starts in making numbers into social practices.Distinktion15 (2):208-222.
  23. Nuffield Council on Bioethics. 2015. The Collection, Linking and Use of Data in Biomedical Research and Health Care: Ethical Issues.
  24. Polonetsky, Jules, and Omer Tene. 2013. Privacy and big data: making ends meet. Stanford Law ReviewOnline65. Available at: http://www.stanfordlawreview.org/online/privacy-and-big-data/privacy-and-big-data. Accessed 4 September 2013.
  25. Public Administration Select Committee. 2014. Statistics and Open Data: Harvesting Unused Knowledge, Empowering Citizens and Improving Public Services. London: The House of Commons.
  26. Pybus, Jennifer, Mark Coté, and Tobias Blanke. 2015. Hacking the social life of Big Data.Big Data & Society2 (2). Available at: http://journals.sagepub.com/doi/full/10.1177/2053951715616649. Accessed 12 May 2016.
  27. Rosenblat, Alex, Kate Wikelius, danah boyd, Seeta Peña Gangadharan, and Corrine Yu. 2014. Data & Civil Rights: Health Primer. Data & Society Research Institute. Available at:http://www.datacivilrights.org/pubs/2014-1030/Health.pdf. Accessed 16 December 2014.
  28. Trottier, Daniel, and David Lyon. 2012.Key features of social media surveillance.In Internet and Surveillance: The Challenges of Web 2.0 and Social Media, edited by Christian Fuchs, Kees Boersma, Anders Albrechtslund and Marisol Sandoval, 89-105. New York: Routledge.
  29. van Dijck, José. 2013. The Culture of Connectivity: A Critical History of Social Media. Oxford: Oxford University Press.
  30. van Dijck, José. 2014. Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology.Surveillance & Society12 (2):197-208.
  31. Vetere, Frank, Martin R. Gibbs, Jesper Kjeldskov, Steve Howard, Florian ‘Floyd’ Mueller, Sonja Pedell, Karen Mecoles, and Marcus Bunyan. 2005. Mediating intimacy: designing technologies to support strong-tie relationships.Proceedings of CHI 2005, Portland, 471-480.
  32. Wellcome Trust. 2013. Summary Report of Qualitative Research into Public Attitudes to Personal Data and Linking Personal Data.http://wellcomelibrary.org/item/b20997358#?c=0&m=0&s=0&cv=0.
  33. Zuboff, Shoshana. 2015. Big other: surveillance capitalism and the prospects of an information civilization.Journal of Information Technology30 (1):75-89