Unblinking eyes: the ethics of automating surveillance

Abstract

In this paper I critique the ethical implications of automating CCTV surveillance. I consider three modes of CCTV with respect to automation: manual (or non-automated), fully automated, and partially automated. In each of these I examine concerns posed by processing capacity, prejudice towards and profiling of surveilled subjects, and false positives and false negatives. While it might seem as if fully automated surveillance is an improvement over the manual alternative in these areas, I demonstrate that this is not necessarily the case. In preference to the extremes I argue in favour of partial automation in which the system integrates a human CCTV operator with some level of automation. To assess the degree to which such a system should be automated I draw on the further issues of privacy and distance. Here I argue that the privacy of the surveilled subject can benefit from automation, while the distance between the surveilled subject and the CCTV operator introduced by automation can have both positive and negative effects. I conclude that in at least the majority of cases more automation is preferable to less within a partially automated system where this does not impinge on efficacy.

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Notes

  1. 1.

    This also does not deny that there might be deep-seated reasons for the shoplifting which should be addressed beyond any judicial punishment for the crime following apprehension.

  2. 2.

    Given that 39% were illegal aliens, 19% had outstanding warrants and 16% were in possession of fraudulent or suspect documents, however, it is questionable as to how much of a threat these individuals posed to airports.

  3. 3.

    An alternative calculation here would determine the false positives at this stage being those identified for secondary screening but not referred to interview (i.e. 138,922) vice those identified for secondary screening but not arrested.

  4. 4.

    Other scales have been proposed, notably that described by Endsley and Kiris (1995). However the Endsley-Kiris scale focuses on aspects of decision-making, while my desire is to focus on the filtering of information.

  5. 5.

    It is important to note that the work of Hogg and Sochman was developed for use in a partially automated system. Its inclusion here is purely illustrative of the possibility of unintended prejudice entering a fully automated system and is hence not intended to be critical of Hogg and Sochman.

  6. 6.

    “To our knowledge, however, the characteristics of the motion of pedestrian groups have not been empirically studied so far. It is basically unknown how moving group members interact with each other, with other pedestrians and with other groups. It also needs to be studied how such groups organize in space and how these spatial patterns affect the crowd dynamics. This is expected to be important for the planning of pedestrian facilities, mass events and evacuation concepts” (Moussaid et al. 2010).

  7. 7.

    “High density” in this context being defined as more than one person per square metre.

  8. 8.

    Quite how the operator would do this in practice need not be of concern for the point at hand.

  9. 9.

    Interestingly, in e-mail correspondence, Clive Norris has suggested that pictures of the faces of all relevant camera operators be posted in the areas in which CCTV is operating in an attempt to overcome this problem.

References

  1. Agre, P. E. (1994). Surveillance and capture: two models of privacy. The Information Society, 10(2), 101–127.

    Article  Google Scholar 

  2. Baker, C. L., Goodman, N. D. & Tenenbaum, J. B. (2008). Theory-based social goal inference. In Proceedings of the thirtieth annual conference of the cognitive science society. Available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.2746. Accessed 11 February, 2012.

  3. Bowker, G. C., & Star, S. L. (2000). Sorting things out: Classification and its consequences. Cambridge: MIT Press.

    Google Scholar 

  4. Burrell, I. (1998). Face-recognition CCTV launched. The Independent. Available at: http://www.independent.co.uk/news/facerecognition-cctv-launched-1178300.html. Accessed 11 February, 2012.

  5. Chattaraj, U., Seyfried, A., & Chakroborty, P. (2009). Comparison of pedestrian fundamental diagram across cultures. Advances in Complex Systems, 12(3), 393–405.

    Article  Google Scholar 

  6. Corby Borough Council Electronic Information Team. (2011). The borough of corby cctv department. http://www.corby.gov.uk/business/towncentremanagement/pages/cctv.aspx. Accessed 17 May, 2011.

  7. Dodd, V. (2010). Stop and search plans are “discriminatory”, watchdog warns. The guardian. Available at: http://www.guardian.co.uk/uk/2010/nov/15/stop-and-search-equality-commission. Accessed 31 March, 2011.

  8. Endsley, M., & Kiris, E. (1995). The out-of-the-loop performance problem and level of control in automation. Human Factors, 37(2), 381–394.

    Article  Google Scholar 

  9. Firth, N. (2011). Face recognition technology fails to find UK rioters. New Scientist, (2826). Available at: http://www.newscientist.com/article/mg21128266.000-face-recognition-technology-fails-to-find-uk-rioters.html. Accessed 11 February, 2012.

  10. Gerrard, G., Parkins, G., Cunningham, I., Jones, W., Hill, S., & Douglas, S. (2007). National CCTV strategy, home office and association of chief police officers. http://webarchive.nationalarchives.gov.uk/20100413151441/http://www.crimereduction.homeoffice.gov.uk/cctv/National%20CCTV%20Strategy%20Oct%202007.pdf. Accessed 21 January, 2011.

  11. Gill, M. & Spriggs, A. (2005). Assessing the impact of CCTV. Home Office. Available at: http://rds.homeoffice.gov.uk/rds/pdfs05/hors292.pdf. Accessed 26 July, 2010.

  12. Graham, S. (1998). Towards the fifth utility? On the extension and normalisation of public CCTV. In C. Norris, J. Moran, & G. Armstrong (Eds.), CCTV, surveillance and social control (pp. 89–112). Aldershot: Ashgate Publishing Limited.

    Google Scholar 

  13. Haggerty, K. D. (2009). Methodology as a knife fight: The process, politics and paradox of evaluating surveillance. Critical Criminology, 17(4), 277–291.

    Article  Google Scholar 

  14. Harwood, M., (2010). Terrorists slip past TSA’s scientifically untested behavioral threat detection program. Security Management. http://www.securitymanagement.com/news/terrorists-slip-past-tsas-scientifically-untested-behavioral-threat-detection-program-007158. Accessed 17 May, 2011.

  15. Helbing, D., Johansson, A., & Al-Abideen, H. (2007). Dynamics of crowd disasters: An empirical study. Physical Review E,. doi:10.1103/PhysRevE.75.046109.

    Google Scholar 

  16. Helbing, D., & Molnar, P. (1995). Social force model for pedestrian dynamics. Physical Review E, 51(5), 4282–4286.

    Article  Google Scholar 

  17. Huang, G.B. et al., (2008). Labeled faces in the wild: A database for studying face recognition in unconstrained environments. Workshop on faces in “real-life” images: detection, alignment, and recognition. Marseille, France. Available at: http://hal.archives-ouvertes.fr/inria-00321923/. Accessed 11 February, 2012.

  18. Keteyian, A. (2010). TSA’s program to spot terrorists a $200 M sham? CBS Evening News. http://www.cbsnews.com/stories/2010/05/19/eveningnews/main6500349.shtml. Accessed 17 May, 2011.

  19. Koushki, P. A. (1988). Walking characteristics in central Riyadh, Saudi Arabia. Journal of Transportation Engineering, 114(6), 735–744.

    Article  Google Scholar 

  20. Lippert-Rasmussen, K. (2010). “We are all different”: Statistical discrimination and the right to be treated as an individual. The Journal of Ethics, 15(1–2), 47–59.

    Google Scholar 

  21. Lord, S. M. (2010). Aviation Security: Efforts to validate TSA’s passenger screening behavior detection program underway but opportunities exist to strengthen validation and address operational challenges, government accountability office. http://www.gao.gov/new.items/d10763.pdf. Accessed 18 January, 2011.

  22. Lyon, D. (2002). Surveillance as social sorting: Computer codes and mobile bodies. In D. Lyon (Ed.), Surveillance as social sorting (pp. 13–30). Oxford: Routledge.

    Google Scholar 

  23. Mack, A. (2003). Inattentional blindness: Looking without seeing. Current Directions in Psychological Science, 12(5), 180–184.

    Article  Google Scholar 

  24. Manning, F. (2011). Worcester city monitor 100 CCTV cameras with only one person. Big Brother Watch. http://www.bigbrotherwatch.org.uk/home/2011/08/worcester-city-monitor-100-cctv-cameras-with-only-one-person.html. Accessed 24 August, 2011.

  25. McKinnon, R. (2007). Big brother isn’t watching. Evening Times. http://www.eveningtimes.co.uk/big-brother-isn-t-watching-1.976256. Accessed 17 May, 2011.

  26. Mica, J.L. (2010). Letter to janet napolitano, secretary, department of homeland security. http://republicans.transportation.house.gov/Media/file/111th/Aviation/2010-05-20-TSA_Reorg_Letter.pdf. Accessed 18 January, 2011.

  27. Michelman, S. (2009). Who can sue over government surveillance? UCLA Law Review, 57, 71–106.

    Google Scholar 

  28. Morrall, J., Ratnayake, L., & Seneviratne, P. (1991). Comparison of CBD pedestrian characteristics in Canada and Sri Lanka. Transportation Research Record, 1294, 57–61.

    Google Scholar 

  29. Moussaid, M., Perozo, N., Garnier, S., Helbing, D., & Theraulaz, G. (2010). The walking behaviour of pedestrian social groups and Its impact on crowd dynamics. PLoS ONE. doi:10.1371/journal.pone.0010047.

    Google Scholar 

  30. Norris, C. (2002). From personal to digital: CCTV, the panopticon, and the technological mediation of suspicion and social control. In D. Lyon (Ed.), Surveillance as social sorting (pp. 249–281). Oxford: Routledge.

    Google Scholar 

  31. Norris, C., & Armstrong, G. (1999). The maximum surveillance society: The rise of CCTV. Oxford: Berg.

    Google Scholar 

  32. Parasuraman, R., Molloy, R., & Singh, I. L. (1993). Performance consequences of automation-induced “complacency”. International Journal of Aviation Psychology, 3(1), 1–23.

    Article  Google Scholar 

  33. Police and Criminal Evidence Act. (1984).

  34. Resnick, R. A. (2002). Change detection. Annual Review of Psychology, 53, 245–277.

    Article  Google Scholar 

  35. Schadschneider, A., Klingsch, W., Klupfel, H., Kretz, T., Rogsch, C., Syfried, A., et al. (2008). Evacuation dynamics: Empirical results, modeling and applications. In B. Meyers (Ed.), Encyclopedia of complexity and system science (pp. 3142–3176). Berlin: Springer.

    Google Scholar 

  36. Simons, D., & Ambinder, M. (2005). Change blindness: theory and consequences. Current Directions in Psychological Science, 14(1), 44–48.

    Article  Google Scholar 

  37. Sochman, J. & Hogg, D., (2010). Who knows who—inverting the social force model for finding groups. IEEE international workshop on socially intelligent surveillance and monitoring (SISM 2011).

  38. Steffen, B. & Syfried, A. (2008) The repulsive force in continuous space models of pedestrian movement. Physics and Society, arXiv:0803.1319v1.

    Google Scholar 

  39. Tanaboriboon, Y., Hwa, S. S., & Chor, C. H. (1986). Pedestrian characteristics study in Singapore. Journal of Transportation Engineering, 112(3), 229–235.

    Article  Google Scholar 

  40. Warikoo, N. (2011). U.S. ends registration program targeting men from muslim countries. The Gazette. http://www.montrealgazette.com/news/canada-in-afghanistan/ends+registration+program+targeting+from+Muslim+countries/4792096/story.html. Accessed 17 May, 2011.

  41. Westacott, E. (2003). Human oversight of surveillance technology. Presentation to the society for philosophy and public affairs, American philosophical association eastern division meeting, Washington DC, 29 December, 2003. https://docs.google.com/Doc?docid=0AWI7P4qhQyVvZGY5OW52dmZfMTgyOHpwZHJrZ3Y&hl=en. Accessed 17 May, 2011.

  42. Winner, L. (1977). Autonomous technology: Technics-out-of-control as a theme for political thought. The Cambridge, MA: MIT Press.

    Google Scholar 

  43. Wiseman, R. (2006). How fast is your city? http://www.richardwiseman.com/quirkology/pace_home.htm. Accessed 20 May, 2011.

  44. Xiaoping, Z., Tingkuan, Z., & Mengting, L. (2009). Modeling crowd evacuation of a building based on seven methodological approaches. Building and Environment, 44(3), 437–445.

    Article  Google Scholar 

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Acknowledgments

The author is grateful for the funding of SUBITO, a European Union FP-7 project, and the University of Leeds for sponsoring this research.

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Correspondence to Kevin Macnish.

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Macnish, K. Unblinking eyes: the ethics of automating surveillance. Ethics Inf Technol 14, 151–167 (2012). https://doi.org/10.1007/s10676-012-9291-0

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Keywords

  • Surveillance
  • Automation
  • CCTV
  • SUBITO
  • Operator
  • Prejudice
  • Profiling
  • False positives
  • False negatives
  • Clive Norris
  • Gary Armstrong