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Privacy Risks and Responses in the Digital Age

  • Josh CowlsEmail author
Chapter
Part of the Digital Ethics Lab Yearbook book series (DELY)

Abstract

Digital devices, the data they collect, and the algorithms that process this data have transformed government, business and everyday life. In this chapter I offer a brief introduction to privacy in the context of American jurisprudence. I then identify major risks to personal privacy that occur at three stages of the “lifecycle” of data: infrastructural asymmetry at the point of data collection, distortion at the point of data analysis, and discrimination at the point of deployment of the insights of data analysis. Having identified these risks, I then introduce a framework consisting of four categories of responses that can be adopted to mitigate them. These categories of responses apply at the level of the individual and of society at large, and in both instrumental and epistemological senses. I conclude by arguing that this framework should serve as a basis for future research into the effects of ICTs on privacy.

Keywords

Privacy Personal data Surveillance Algorithms 

References

  1. Angwin, J., J. Larson, S. Mattu, and L. Kirchner. 2016, May 23. Machine bias. ProPublica. Retrieved January 13, 2018, from https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
  2. Balaram, B. 2017, October 4. The role of citizens in developing ethical AI. The Royal Society for the Arts. Accessible at: https://www.thersa.org/discover/publications-and-articles/rsa-blogs/2017/10/the-role-of-citizens-in-developing-ethical-ai
  3. Botsman, Rachel. 2017, October, 21. Big data meets big brother as China moves to rate its citizens. Wired. Accessible at: https://www.wired.co.uk/article/chinese-government-social-credit-score-privacy-invasion
  4. Brandeis, L.D. 2009. Other people’s money and how the bankers use it. Cosimo.Google Scholar
  5. Brucato, B. 2015. The new transparency: Police violence in the context of ubiquitous surveillance. Media and Communication 3 (3).CrossRefGoogle Scholar
  6. Curtis, Sophie. 2015, November, 23. How much is your personal data worth? The telegraph. Accessible at: https://www.telegraph.co.uk/technology/news/12012191/How-much-is-your-personal-data-worth.html
  7. Diakopoulos, N. 2015. Algorithmic accountability: Journalistic investigation of computational power structures. Digital Journalism 3 (3): 398–415.CrossRefGoogle Scholar
  8. Floridi, L. 2005. The ontological interpretation of informational privacy. Ethics and Information Technology 7 (4): 185–200.CrossRefGoogle Scholar
  9. ———. 2016. On human dignity as a foundation for the right to privacy. Philosophy & Technology 29 (4): 307–312.CrossRefGoogle Scholar
  10. ———. 2017. Digital’s cleaving power and its consequences. Philosophy & Technology 30 (2): 123–129.CrossRefGoogle Scholar
  11. Floyd v. City of New York, 959 F. Supp. 2d 540 (S.D.N.Y. 2013).Google Scholar
  12. Garvie, C., and J. Frankle. 2016. Facial-recognition software might have a racial bias problem. The Atlantic. Accessible at https://www.theatlantic.com/technology/archive/2016/04/the-underlying-bias-of-facial-recognition-systems/476991/
  13. Glancy, D.J. 1979. Invention of the right to privacy. The Arizona Law Review 21: 1.Google Scholar
  14. Gibbs, Samuel. 2018, March, 7. Google’s AI is being used by US military drone programme. The Guardian. Accessible at: https://www.theguardian.com/technology/2018/mar/07/google-ai-us-department-of-defensemilitary-drone-project-maven-tensorflow
  15. Goodman, B., and S. Flaxman. 2016, June. EU regulations on algorithmic decision-making and a “right to explanation”. In ICML Workshop on Human Interpretability in machine learning (WHI 2016), New York. Accessible at http://arxiv.org/abs/1606.08813.
  16. Hildebrandt, Mireille. 2006. Privacy and identity. In Privacy and the criminal law, ed. Erik Claes, Antony Duff, and Serge Gutwirth. Oxford: Intersentia.Google Scholar
  17. Hobbes, T. 2006 [1651]. Leviathan. A&C Black.Google Scholar
  18. Hunt, E. 2016. Tay, Microsoft’s AI chatbot, gets a crash course in racism from Twitter. The Guardian. Accessible at https://www.theguardian.com/technology/2016/mar/24/tay-microsofts-ai-chatbot-gets-a-crash-course-in-racism-from-twitter
  19. Katz v. United States, 389 U.S. 347 (1967).Google Scholar
  20. Laughland, O., K. Epstein, and J. Glenza. 2014, December 5. The Guardian. Accessible at https://www.theguardian.com/us-news/2014/dec/05/eric-garner-case-new-york-protests-continue-through-second-night
  21. Lomas, N. 2017. Google’s right to be forgotten appeal heading to Europe’s top court. TechCrunch. Accessible at https://techcrunch.com/2017/07/19/googles-right-to-be-forgotten-appeal-heading-to-europes-top-court/
  22. Mann, S. 2004, October. Sousveillance: Inverse surveillance in multimedia imaging. In Proceedings of the 12th annual ACM International conference on multimedia, 620–627. ACM.Google Scholar
  23. Masse, B. 2017, Sepetember 12. What’s the worst that could happen with huge databases of facial biometric data? Gizmodo. Accessible at https://www.gizmodo.com.au/2017/09/whats-the-worst-that-could-happen-with-huge-databases-of-facial-biometric-data/
  24. MIT. 2017. The moral machine. Accessible at: http://moralmachine.mit.edu
  25. Mittelstadt, B.D., P. Allo, M. Taddeo, S. Wachter, and L. Floridi. 2016. The ethics of algorithms: Mapping the debate. Big Data & Society 3 (2): 2053951716679679.CrossRefGoogle Scholar
  26. Nakashima, E. 2016. Apple vows to resist FBI demand to crack iPhone linked to San Bernardino attacks. Washington Post. Accessible at https://www.washingtonpost.com/world/national-security/us-wants-apple-to-help-unlock-iphone-used-by-san-bernardino-shooter/2016/02/16/69b903ee-d4d9-11e5-9823-02b905009f99_story.html
  27. New York Times Co. v. United States, 403 U.S. 713 (1971).Google Scholar
  28. Nissenbaum, H. 2009. Privacy in context: Technology, policy, and the integrity of social life. Stanford: Stanford University Press.Google Scholar
  29. O’Neill, C. 2016. Weapons of math destruction. How big data increases inequality and threatens democracy. New York: Random House Audio.Google Scholar
  30. Olmstead v. United States, 277 U.S. 438 (1928).Google Scholar
  31. Panday. 2017, August 28. India’s Supreme Court upholds right to privacy as a fundamental right – and it’s about time. Electronic Frontier Foundation. Accessible at https://www.eff.org/deeplinks/2017/08/indias-supreme-court-upholds-right-privacy-fundamental-right-and-its-about-time
  32. Posner, R.A. 1978. Economic theory of privacy. Regulation 2: 19.Google Scholar
  33. Puttaswamy v. Union of India. 2017. Writ Petition (Civil) No. 494 of 2012.Google Scholar
  34. Schneier, B. 2015. Data and goliath: The hidden battles to collect your data and control your world. New York: WW Norton.Google Scholar
  35. Singh, A., D. Patil, G.M. Reddy, and S.N. Omkar. 2017. Disguised Face Identification (DFI) with facial keypoints using spatial fusion convolutional network. arXiv:1708.09317v1 [cs.CV].Google Scholar
  36. Solove, D.J. 2005. A taxonomy of privacy. University of Pennsylvania Law Review 154: 477.CrossRefGoogle Scholar
  37. Taylor, L., L. Floridi, and B. van der Sloot, eds. 2016. Group privacy: New challenges of data technologies. Cham: Springer.Google Scholar
  38. Thomson, J.J. 1975. The right to privacy. Philosophy and Public Affairs 4 (4): 295–314.CrossRefGoogle Scholar
  39. Wachter, S., B. Mittelstadt, and L. Floridi. 2017a. Transparent, explainable, and accountable AI for robotics. Science robotics 2 (6): eaan6080.CrossRefGoogle Scholar
  40. Wachter, S., B. Mittelstadt, and C. Russell. 2017b. Counterfactual explanations without opening the black box: Automated decisions and the GDPR. arXiv:1711.00399.Google Scholar
  41. Warren, S.D., and L.D. Brandeis. 1890. The right to privacy. Harvard Law Review 4: 193–220.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Oxford Internet Institute, Digital Ethics LabUniversity of OxfordOxfordUK
  2. 2.The Alan Turing InstituteLondonUK

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