Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-27T11:59:51.681Z Has data issue: false hasContentIssue false
  • English
  • Français

Governing others: Anomaly and the algorithmic subject of security

Published online by Cambridge University Press:  01 November 2017

Claudia Aradau  and
Tobias Blanke
Claudia Aradau*
Affiliation:
Professor, International Politics, King’s College London
Tobias Blanke
Affiliation:
Reader, Social and Cultural Informatics, King’s College London
*
*Correspondence to: Claudia Aradau, Professor of International Politics, Dept. of War Studies, King’s College London, Strand, London WC2R 2LS. Author’s email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

As digital technologies and algorithmic rationalities have increasingly reconfigured security practices, critical scholars have drawn attention to their performative effects on the temporality of law, notions of rights, and understandings of subjectivity. This article proposes to explore how the ‘other’ is made knowable in massive amounts of data and how the boundary between self and other is drawn algorithmically. It argues that algorithmic security practices and Big Data technologies have transformed self/other relations. Rather than the enemy or the risky abnormal, the ‘other’ is algorithmically produced as anomaly. Although anomaly has often been used interchangeably with abnormality and pathology, a brief genealogical reading of the concept shows that it works as a supplementary term, which reconfigures the dichotomies of normality/abnormality, friend/enemy, and identity/difference. By engaging with key practices of anomaly detection by intelligence and security agencies, the article analyses the materialisation of anomalies as specific spatial ‘dots’, temporal ‘spikes’, and topological ‘nodes’. We argue that anomaly is not simply indicative of more heterogeneous modes of othering in times of Big Data, but represents a mutation in the logics of security that challenge our extant analytical and critical vocabularies.

Keywords

AlgorithmsBig DataSecuritySelf/OtherSurveillanceAnomaly
Type
Research Article
Information
European Journal of International Security , Volume 3 , Issue 1 , February 2018 , pp. 1 - 21
Copyright
© British International Studies Association 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1 Department of Defence, ‘Protecting the Force: Lessons from Fort Hood’ (2010), available at: {http://www.defense.gov/Portals/1/Documents/pubs/DOD-ProtectingTheForce-Web_Security_HR_13Jan10.pdf} accessed 30 June 2016.

2 MacLeish, Kenneth T., Making War at Fort Hood: Life and Uncertainty in a Military Community (Princeton: Princeton University Press, 2013), p. 186 Google Scholar.

3 William H. Webster Commission, Final Report of the William H. Webster Commission on The Federal Bureau of Investigation, Counterterrorism Intelligence, and the Events at Fort Hood, Texas, on November 5, 2009 (Federal Bureau of Investigation, 2012), p. 8, available at: {https://www.hsdl.org/?view&did=717443} accessed on 15 July 2017.

4 Joseph I. Lieberman, Ticking Time Bomb: Counter-Terrorism Lessons from the US Government’s Failure to Prevent the Fort Hood Attack (2011), available at: {https://www.hsgac.senate.gov/imo/media/doc/Fort_Hood/FortHoodReport.pdf} accessed on 16 July 2017.

5 Defense Advanced Research Projects Agency (DARPA), ‘Anomaly Detection at Multiple Scales (ADAMS)’ (2010), available at: {https://www.fbo.gov/download/2f6/2f6289e99a0c04942bbd89ccf242fb4c/DARPA-BAA-11-04_ADAMS.pdf} accessed 26 February 2016.

6 UK Home Department, ‘Draft Investigatory Powers Bill’, Her Majesty’s Stationery Office (2015), p. 20, available at: {https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/473770/Draft_Investigatory_Powers_Bill.pdf } accessed 16 July 2017.

7 David Anderson QC, Report of the Bulk Powers Reviews, Independent Reviewer of Terrorism Legislation (2016), available at: {https://terrorismlegislationreviewer.independent.gov.uk/wp-content/uploads/2016/08/Bulk-Powers-Review-final-report.pdf} accessed 30 August 2016.

8 Akoglu, Leman, Tong, Hanghang, and Koutra, Danai, ‘Graph based anomaly detection and description: a survey’, Data Mining and Knowledge Discovery, 29:3 (2015), p. 626 CrossRefGoogle Scholar.

9 DARPA, ‘Anomaly Detection at Multiple Scales’, p. 2.

10 NSA, ‘Data Scientist. Job Description’ (2016), available at: {https://www.nsa.gov/psp/applyonline/EMPLOYEE/HRMS/c/HRS_HRAM.HRS_CE.GBL?Page=HRS_CE_JOB_DTL&Action=A&JobOpeningId=1076263&SiteId=1&PostingSeq=1} accessed 16 October 2016.

11 Amoore, Louise, The Politics of Possibility: Risk and Security beyond Probability (Durham, NC: Duke University Press, 2013)CrossRefGoogle Scholar; de Goede, Marieke, Speculative Security: The Politics of Pursuing Terrorist Monies (Minneapolis: University of Minnesota Press, 2012)Google Scholar; Aradau, Claudia and van Munster, Rens, Politics of Catastrophe: Genealogies of the Unknown (Abingdon: Routledge, 2011)CrossRefGoogle Scholar; Bauman, Zygmunt et al., ‘After Snowden: Rethinking the impact of surveillance’, International Political Sociology, 8:2 (2014), pp. 21–144 CrossRefGoogle Scholar; Bigo, Didier, ‘The (in)securitization practices of the three universes of EU border control: Military/navy – border guards/police – database analysts’, Security Dialogue, 45:3 (2014), pp. 209–225 Google Scholar; Huysmans, Jef, ‘Democratic curiosity in times of surveillance’, European Journal of International Security, 1:1 (2016), pp. 73–93 Google Scholar; Lyon, David, Surveillance After Snowden (Cambridge: Polity, 2015)Google Scholar.

12 Lohr, Steve, Data-ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else (New York: Harper Collins, 2015), p. 8 Google Scholar.

13 The digitisation of identity and the body as data have been key areas of critical research around biometrics, mobility, and border control. See, for example, Epstein, Charlotte, ‘Guilty bodies, productive bodies, destructive bodies: Crossing the biometric borders’, International Political Sociology, 1:2 (2007), pp. 149–164 Google Scholar; Muller, Benjamin J., Security, Risk and the Biometric State: Governing Borders and Bodies (Abingdon: Routledge, 2009)CrossRefGoogle Scholar. In this article, we are interested in the epistemic production of subjects of (in)security through algorithmic techniques that move beyond the biometric identification of individuals to compute massive, structured and unstructured, data at scale. See Amoore, The Politics of Possibility; Lyon, David, ‘Surveillance, Snowden, and Big Data: Capacities, consequences, critique’, Big Data & Society, 1:2 (2014), pp. 1–13 Google Scholar; Aradau, Claudia and Blanke, Tobias, ‘The (Big) Data-security assemblage: Knowledge and critique’, Big Data & Society, 2:2 (2015), pp. 1–12 CrossRefGoogle Scholar; Crampton, Jeremy W, ‘Collect it all: National security, Big Data and governance’, GeoJournal, 80:4 (2015), pp. 519–531 Google Scholar.

14 Amoore, , The Politics of Possibility, p. 113 CrossRefGoogle Scholar.

15 We use logics here in Foucault’s sense of ‘the logic of connections between the heterogeneous’. Foucault, Michel, The Birth of Biopolitics: Lectures at the College de France, 1978–1979 (Basingstoke: Palgrave Macmillan, 2008), p. 42 CrossRefGoogle Scholar.

16 Campbell, David, Writing Security: United States Foreign Policy and the Politics of Identity (Manchester: Manchester University Press, 1992), p. 7 CrossRefGoogle Scholar.

17 Williams, Michael C. and Krause, Keith, ‘Preface: Toward critical security studies’, in Keith Krause and Michael C. Williams (eds), Critical Security Studies: Concepts and Cases (London: UCL Press, 1997) , p. xv Google Scholar.

18 Derian, James Der, Critical Practices in International Theory: Selected Essays (London: Routledge, 2009), p. 151 Google Scholar. Consequently, less antagonistic understandings of difference are needed to unmake security.

19 Jabri, Vivienne, War and the Transformation of Global Politics (Basingstoke: Palgrave Macmillan, 2007), p. 12 CrossRefGoogle Scholar.

20 Huysmans, Jef, The Politics of Insecurity: Fear, Migration and Asylum in the EU (London: Routledge, 2006), p. 50 Google Scholar.

21 Stern, Maria, ‘“We” the subject: the power and failure of (in)security’, Security Dialogue, 37:2 (2006), p. 193 Google Scholar.

22 Hansen, Lene, Security as Practice: Discourse Analysis and the Bosnian War (London: Routledge, 2006), p. 36 Google ScholarPubMed.

23 Some of the literature on European integration has distinguished forms of spatial and temporal othering. See, for example, Diez, Thomas, ‘Constructing the self and changing others: Reconsidering normative power Europe’, Millennium: Journal of International Studies, 33:3 (2005), pp. 319–335 CrossRefGoogle Scholar. For a critique of the distinction between space and time in the construction of Europe’s others, see Prozorov, Sergei, ‘The other as past and present: Beyond the logic of “temporal othering” in IR theory’, Review of International Studies, 37:3 (2011), pp. 1273–1293 CrossRefGoogle Scholar. Barry Hindess has developed one of the most cogent articulations of the relation between time and others: Hindess, Barry, ‘The past is another culture’, International Political Sociology, 1:4 (2007), pp. 325–338 Google Scholar.

24 Campbell, , Writing Security, p. 94 Google Scholar.

25 Balzacq, Thierry et al., ‘Security practices’, in Robert A. Denemark (ed.), International Studies Encyclopedia (Blackwell, 2010)Google Scholar, available at: {http://www.isacompendium.com/public/book.html?id=g9781444336597_yr2013_978144433659}; Bueger, Christian, ‘Making things known: Epistemic practices, the United Nations, and the translation of piracy’, International Political Sociology, 9:1 (2015), pp. 1–18 CrossRefGoogle Scholar; Davidshofer, Stephan, Jeandesboz, Julien, and Ragazzi, Francesco, ‘Technology and security practices: Situating the technological imperative’, in Tugba Basaran et al. (eds), International Political Sociology: Transversal Lines (London: Routledge, 2016), pp. 205–227 CrossRefGoogle Scholar; Huysmans, , ‘Democratic curiosity in times of surveillance’; Didier Bigo, ‘Freedom and speed in enlarged borderzones’, in Vicki Squire (ed.), The Contested Politics of Mobility: Borderzones and Irregularity (London: Routledge, 2010), pp. 31–50 Google Scholar; Amicelle, Anthony, Aradau, Claudia, and Jeandesboz, Julien, ‘Questioning security devices: Performativity, resistance, politics’, Security Dialogue, 46:5 (2015), pp. 293–306 Google Scholar.

26 Bigo, ‘The (in)securitization practices of the three universes of EU border control’.

27 Ibid., p. 216.

28 This is not to say that these architectures of difference exist in separate worlds, as Bigo’s analysis of separate, but competing professional universes would indicate. On the distinction between an analysis focused on professionals and analyses of expertise, see Eyal, Gil and Pok, Grace, ‘What is security expertise?’, in Trine Villumsen Berling and Christian Bueger (eds), Security Expertise: Practice, Power, Responsibility (London: Routledge, 2015), pp. 37–59 CrossRefGoogle Scholar.

29 Bauman, Zygmunt and Lyon, David, Liquid Surveillance: A Conversation (Cambridge: Polity, 2013)Google Scholar. The formulation of ‘data doubles’ is usually accredited to Haggerty and Ericson’s seminal article Haggerty, Kevin D. and Ericson, Richard V, ‘The surveillant assemblage’, The British Journal of Sociology, 51:4 (2000), pp. 605–622 Google Scholar.

30 Amoore, Louise, ‘Biometric borders: Governing mobilities in the war on terror’, Political Geography, 25:3 (2006), p. 339 Google Scholar.

31 Harcourt, Bernard E., Exposed: Desire and Disobedience in the Digital Age (Cambridge, MA: Harvard University Press, 2015), p. 343 Google Scholar.

32 Chamayou, Grégoire, A Theory of the Drone (New York: The New Press, 2015), p. 87 Google Scholar.

33 DARPA, ‘Anomaly Detection at Multiple Scales’, p. 6 Google Scholar.

34 McCue, Colleen, Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis (2nd edn, Oxford: Butterworth-Heinemann, 2015), p. 87 CrossRefGoogle Scholar. McCue is described in the media as a ‘pioneer in data analytics’ and credited with helping catch the Virginia sniper in 2011. Data-Smart City Solutions, ‘Dr. Colleen McCue: Pioneer in Data Analytics’ (2013), available at: {http://datasmart.ash.harvard.edu/news/article/dr.-colleen-mccue-pioneer-in-data-analytics-133} accessed 14 September 2016.

35 Government Communications Head Quarters (GCHQ), ‘GCHQ Analytic Cloud Challenges’ (2012), available at: {https://search.edwardsnowden.com/docs/GCHQAnalyticCloudChallenges2015-09-25nsadocs} accessed 20 February 2016.

36 Communications Security Establishment Canada, ‘CSEC SIGINT Cyber Discovery: Summary of the Current Effort’, Snowden Archive (2010), available at: {https://search.edwardsnowden.com/docs/CSECSIGINTCyberDiscoverySummaryofthecurrenteffort2015-01-17nsadocs} accessed 30 June 2016.

37 GCHQ, ‘GCHQ Analytic Cloud Challenges’.

38 GCHQ, ‘HIMR Data Mining Research Problem Book’, Snowden Archive (2011), available at: {https://edwardsnowden.com/wp-content/uploads/2016/02/Problem-Book-Redacted.pdf} accessed 27 April 2016.

39 Ibid., p. 30.

40 NSA, ‘XKeyScore’, Snowden Archive (2008), available at: {https://search.edwardsnowden.com/docs/XKeyScore2013-07-31nsadocs} accessed 30 June 2016. Compar anomaly detectiion with techniques of sensing that which is ‘out of place’. Aradau and van Munster, Politics of Catastrophe, ch. 6.

41 Chandola, Varun, Banerjee, Arindam, and Kumar, Vipin, ‘Anomaly detection: a survey’, ACM Computing Surveys, 41:3 (2009), pp. 1–58 CrossRefGoogle Scholar.

42 Grubbs, Frank E., ‘Procedures for detecting outlying observations in samples’, Technometrics, 11:1 (1969), p. 1 Google Scholar.

43 Agyemang, Malik, Barker, Ken, and Alhajj, Rada, ‘A comprehensive survey of numeric and symbolic outlier mining techniques’, Intelligent Data Analysis, 10:6 (2006), pp. 521–538 Google Scholar.

44 Daroczi, Gergely, Mastering Data Analysis with R (Birmingham, UK: Packt Publishing, 2015), p. 291 Google Scholar.

45 Aggarwal, Charu C., Outlier Analysis (New York: Springer, 2013), p. 43 Google Scholar.

46 Eberle, William and Holder, Lawrence, ‘Anomaly detection in data represented as graphs’, Intelligent Data Analysis, 11:6 (2007), pp. 663–689 CrossRefGoogle Scholar; Akhgar, Babak et al. (eds), Application of Big Data for National Security: A Practitioner’s Guide to Emerging Technologies (Amsterdam: Butterworth-Heinemann, 2015)Google Scholar; Akoglu, Tong, and Koutra, ‘Graph based anomaly detection and description’.

47 Akoglu, , Tong, , and Koutra, , ‘Graph based anomaly detection and description’, p. 627 CrossRefGoogle Scholar.

48 Chandola, , Banerjee, , and Kumar, , ‘Anomaly detection’, p. 1. In the computing literature, the turning point for research on anomalies themselves is located around 2000. Markus Goldstein and Seiichi Uchida, ‘A comparative evaluation of unsupervised anomaly detection algorithms for multivariate data’, PloS one, 11:4 (2016), e0152173 Google Scholar.

49 Aggarwal, , Outlier Analysis, p. 1 CrossRefGoogle Scholar.

50 Chandola, Banerjee, and Kumar, ‘Anomaly detection’.

51 Agyemang, , Barker, , and Alhajj, , ‘A comprehensive survey of numeric and symbolic outlier mining techniques’, p. 535 Google Scholar.

52 Barnett, Vic and Lewis, Toby, Outliers in Statistical Data (New York: John Wiley & Sons, 1978), p. 7 CrossRefGoogle Scholar.

53 Hacking, Ian, The Taming of Chance (Cambridge: Cambridge University Press, 1990), p. 23 Google Scholar.

54 Link, Jürgen, ‘From the “power of the norm” to “flexible normalism”: Considerations after Foucault’, Cultural Critique, 57:1 (2004), p. 18 Google Scholar. In that sense, normal and normality are distinct from norm and normativity. While the former concepts are entwined to the emergence of statistics in data-processing societies, Link argues that the latter are characteristic of all societies, although they take historically different forms.

55 Ernst, Waltraud, ‘The normal and the abnormal: Reflections on norms and normativity’, in Waltraud Ernst (ed.), Histories of the Normal and the Abnormal: Social and Cultural Histories of Norms and Normativity (Abingdon: Routledge, 2006), p. 10 Google Scholar.

56 Rose, Nikolas, ‘The neurochemical self and its anomalies’, in Richard V. Ericson and Aaron Doyle (eds), Risk and Morality (Toronto: University of Toronto Press, 2003), p. 421 Google Scholar. On the production of the abnormal in the nineteenth century, see also Foucault, Michel, Abnormal: Lectures at the College de France, 1974–1975, trans. Graham Burchell (Basingstoke: Palgrave Macmillan, 2004)Google Scholar.

57 Desrosières, Alain, The Politics of Large Numbers: A History of Statistical Reasoning, trans. Camille Naish (Cambridge, MA: Harvard University Press, 2002), p. 79 Google Scholar.

58 Ibid.

59 Ewald, François, ‘Norms, discipline and the law’, Representations, 30 (1990), p. 146 Google Scholar.

60 Canguilhem, Georges, The Normal and the Pathological (New York: Zone Books, 1991)Google Scholar.

61 Ibid., p. 131.

62 Ibid., p. 136.

63 Kuhn, Thomas S., The Structure of Scientific Revolutions (Chicago: University of Chicago Press, 2012 [orig. pub. 1962])Google Scholar.

64 Rose, ‘The neurochemical self and its anomalies’.

65 For analyses of these anticipatory techniques and limitations of statistical knowledge, see Amoore, The Politics of Possibility; Aradau and van Munster, Politics of Catastrophe; de Goede, Speculative Security.

66 Nancy, Jean-Luc, ‘Préface’, in Camille Fallen (ed.), L’Anomalie Créatrice (Paris: Éditions Kimé, 2012), p. 7 Google Scholar.

67 Hayles, N. Katherine, How We Think: Digital Media and Contemporary Technogenesis (Chicago: University of Chicago Press, 2012), p. 74 CrossRefGoogle Scholar.

68 Aggarwal, , Outlier Analysis, p. 2 Google Scholar.

69 To develop a thick description of these techniques, we have used a combination of the Snowden documents, recently declassified materials, and operational cases made by the UK government in support of the Investigatory Power Bill, independent evaluation reports, and have juxtaposed their claims to the computing literature. We have particularly relied on computer science survey papers on anomaly or outlier detection, which are key forms of knowledge production in the discipline and are most often cited.

70 Hodge, Victoria J. and Austin, Jim, ‘A survey of outlier detection methodologies’, Artificial Intelligence Review, 22:2 (2004), p. 85 CrossRefGoogle Scholar.

71 Chandola, , Banerjee, , and Kumar, , ‘Anomaly detection’, pp. 7–8 Google Scholar.

72 NSA, ‘SKYNET: Courier Detection via Machine Learning’ (2012), available at: {https://search.edwardsnowden.com/docs/SKYNETCourierDetectionviaMachineLearning2015-05-08nsadocs} accessed 20 July 2016.

73 Chandola, , Banerjee, , and Kumar, , ‘Anomaly detection’, p. 27 Google Scholar.

74 Ibid., p. 6.

75 Aggarwal, , Outlier Analysis, p. 101 Google Scholar.

76 Claudia Aradau and Tobias Blanke, ‘Politics of prediction: Security and the time/space of governmentality in the age of Big Data’, European Journal of Social Theory, 20:3 (2017), pp. 373–91.

77 Zhang, Tian, Ramakrishnan, Raghu, and Livny, Miron, ‘BIRCH: a new data clustering algorithm and its applications’, Data Mining and Knowledge Discovery, 1:2 (1996), p. 114 Google Scholar; GCHQ, ‘HIMR Data Mining Research Problem Book’ .

78 Clutterbuck, Richard L., Terrorism in an Unstable World (London: Routledge, 1994), p. 65 Google Scholar.

79 McCue, Colleen, Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis (Oxford: Butterworth-Heinemann, 2006), p. 102 Google Scholar.

80 Ibid., p. 104.

81 Ibid., p. 106.

82 Ibid., p. 110.

83 Chandola, , Banerjee, , and Kumar, , ‘Anomaly detection’, p. 43 Google Scholar.

84 Donald A. Borrmann et al., ‘The History of Traffic Analysis: World War I – Vietnam’, National Security Agency (2013), p. 3, available at: {http://www.nsa.gov/about/_files/cryptologic_heritage/publications/misc/traffic_analysis.pdf} accessed 2 September 2016.

85 Kahn, David, The Codebreakers: The Comprehensive History of Secret Communication from Ancient Times to the Internet (New York: Simon and Schuster, 1996), p. 84 Google Scholar.

86 Home Office, ‘Operational Case for Bulk Powers’, UK Government (2016), p. 35, available at: {https://www.gov.uk/government/publications/investigatory-powers-bill-overarching-documents} accessed 1 March 2016.

87 GCHQ, ‘HIMR Data Mining Research Problem Book’, p. 26.

88 Schneier, Bruce, Data and Goliath: The Hidden Battles to Collect your Data and Control your World (New York: W. W. Norton & Company, 2015), pp. 39–40 Google Scholar.

89 Aggarwal, , Outlier Analysis, p. 224 Google Scholar.

90 Ibid., p. 229.

91 Arun Kejariwal, ‘Introducing Practical and Robust Anomaly Detection in a Time Series’ (2015), available at: {https://blog.twitter.com/2015/introducing-practical-and-robust-anomaly-detection-in-a-time-series} accessed 30 June 2016.

92 Ibid, available at: {https://g.twimg.com/blog/blog/image/figure_raw_residual_global_local.png} accessed 13 October 2017.

93 Manuel Egele, Gianluca Stringhini, Christopher Kruegel, and Giovanni Vigna, ‘COMPA: Detecting Compromised Accounts on Social Networks’ (2013), available at: {http://www.seclab.tuwien.ac.at/papers/compa-ndss13.pdf} accessed 2 October 2016.

94 Chandler, David, ‘A world without causation: Big Data and the coming of age of posthumanism’, Millennium: Journal of International Studies, 43:3 (2015), pp. 833–851 Google Scholar.

95 Home Office, ‘Operational Case for Bulk Powers’, p. 37 Google Scholar.

96 See the discussion of social network analysis as risk technology in de Goede, Marieke, ‘Fighting the network: a critique of the network as a security technology’, Distinktion: Journal of Social Theory, 13:3 (2012), pp. 215–232 Google Scholar.

97 Home Office, ‘Operational Case for Bulk Powers’, p. 28 Google Scholar.

98 GCHQ, ‘HIMR Data Mining Research Problem Book’, p. 12. A 2011 NSA memo revealed by Snowden shows that NSA contact chaining using metadata can be extended from any selector, independent of location and nationality. Previous guidance limited contact chaining to foreign selectors. NSA, ‘New Contact-Chaining Procedures to Allow Better, Faster Analysis’ (2011), available at: {https://search.edwardsnowden.com/docs/NewContact-ChainingProcedurestoAllowBetterFasterAnalysis2013-09-28nsadocs} accessed 8 November 2016.

99 Goldstein, and Uchida, , ‘A comparative evaluation of unsupervised anomaly detection’, p. 2 Google Scholar.

100 NSA, ‘SKYNET’.

101 Christian Grothoff and J. M. Porup, ‘The NSA’s SKYNET Program may be Killing Thousands of Innocent People’, Ars Technica (2016), available at: {http://arstechnica.co.uk/security/2016/02/the-nsas-skynet-program-may-be-killing-thousands-of-innocent-people/} accessed 21 June 2016.

102 NSA, ‘SKYNET’: Courier Detection via Machine Learning’.

103 Chun, Wendy Hui Kyong, Updating to Remain the Same: Habitual New Media (Cambridge, MA: MIT Press, 2016), p. 17 Google Scholar.

104 Chamayou, , A Theory of the Drone, p. 48 Google Scholar.

105 Grothoff and Porup, ‘The NSA’s SKYNET Program’.

106 Ibid.

107 GCHQ, ‘HIMR Data Mining Research Problem Book’, p. 46 Google Scholar.

108 Aggarwal, , Outlier Analysis, p. 353 Google Scholar.

109 Ibid., p. 6.

110 As Anthony Amicelle has brilliantly shown in the case of financial practices for counterterrorism, different understandings of normality and abnormality are not mutually exclusive, but underpin different types of knowledge in financial policing. Anthony Amicelle, ‘Bringing the abnormal back in: On surveillance and financial intelligence’ (forthcoming), author manuscript.

111 Gillespie, Tarleton, ‘The relevance of algorithms’, in Tarleton Gillespie, Pablo J. Boczkowski, and Kirsten A. Foot (eds), Media Technologies: Essays on Communication, Materiality, and Society (Cambridge, MA: MIT Press, 2014), p. 168 Google Scholar.

112 Huysmans, ‘Democratic curiosity in times of surveillance’.

113 Desrosières, The Politics of Large Numbers, p. 401 Google Scholar.

114 District of Columbia District Court, Case No. 1:17-cv-00581, Ahmad Zaidan et al. v Trump (2017), available at: {http://www.politico.com/f/?id=0000015b-2107-d4bd-a5df-bbd7ec5b0001} accessed 14 October 2017.