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Unblinking eyes: the ethics of automating surveillance


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

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

  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.


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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).

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