Risk Profiling by Law Enforcement Agencies in the Big Data Era: Is There a Need for Transparency?

  • Sascha van SchendelEmail author
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 547)


This paper looks at the use of risk profiles by law enforcement in the age of Big Data. First, the paper discusses different use-types of risk profiling. Subsequently, the paper deals with the following three categories of challenges of risk profiling: (a) false positives (and to some extent false negatives) as well as incorrect data and erroneous analysis, (b) discrimination and stigmatization, (c) and maintaining appropriate procedural safeguards. Based on the hypothesis of risk profiling creating challenges, this paper addresses the question whether we need transparency of risk profiling by law enforcement actors, from the perspective of protecting fundamental rights of those affected by the use of risk profiles. The paper explores tackling these challenges from the angle of transparency, introducing Heald’s varieties of transparency as a theoretical model.


Risk profiling Transparency Law enforcement Procedural safeguards False positives Discrimination Data protection Criminal law Explanation 


  1. 1.
    van der Sloot, B., van Schendel, S.: International and Comparative Study on Big Data, Working Paper no. 20, Dutch Scientific Council for Government Policy (WRR) (2016)Google Scholar
  2. 2.
    Marks, A., Bowling, B., Keenan, C.: Automatic justice? Technology, crime and social control. In: Brownsword, R., Scotford, E., Yeung, K. (eds.) The Oxford Handbook of the Law and Regulation of Technology. OUP (2017)Google Scholar
  3. 3.
    Kemshall, H.: Understanding Risk in Criminal Justice. Crime and Justice Series. Open University Press, London (2003)Google Scholar
  4. 4.
    Reichman, N.: Managing crime risk: towards an insurance based model of social control. Res. Law Soc. Control 8, 151–172 (1986)Google Scholar
  5. 5.
    Harcourt, B.E.: Against Prediction Profiling, Policing, and Punishing in an Actuarial Age. The University of Chicago Press (2007)Google Scholar
  6. 6.
    Ericson, R.V., Haggerty, E.: Policing the Risk Society. Clarendon Press, Oxford (1997)Google Scholar
  7. 7.
    Koops, E.J.: Technology and the crime society: rethinking legal protection. Law Innov. Technol. 1, 93–124 (2009)CrossRefGoogle Scholar
  8. 8.
    Zouave, E.T., Marquenie, T.: An inconvenient truth: algorithmic transparency & accountability in criminal intelligence profiling. In: 2017 European Intelligence and Security Informatics Conference (2017)Google Scholar
  9. 9.
    Heald, D.: Varieties of transparency. In: Hood, C., Heald, D. (eds.) Transparency: The Key to Better Governance? OUP/British Academy (Proceedings of the British Academy) (2006)Google Scholar
  10. 10.
    Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) L 119/1Google Scholar
  11. 11.
    Directive (EU) 2016/680 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data by competent authorities for the purposes of the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, and on the free movement of such data, and repealing Council Framework Decision 2008/977/JHA, L 119/89Google Scholar
  12. 12.
    Brkan, M.: Do algorithms rule the world? Algorithmic decision-making in the framework of the GDPR and beyond, 1 August 2017. SSRN:
  13. 13.
  14. 14.
    van Brakel, R.: Pre-emptive big data surveillance and its (dis)empowering consequences: the case of predictive policing. In: van der Sloot, B., et al. (eds.) Exploring the Boundaries of Big Data. Amsterdam University Press, Amsterdam (2016)Google Scholar
  15. 15.
    Besluit SUWI: Staatsblad, 320 (2014).
  16. 16.
  17. 17.
  18. 18.
    Hildebrandt, M.: Defining profiling: a new type of knowledge? In: Hildebrandt, M., Gutwirth, S. (eds.) Profiling the European Citizen, pp. 17–45. Springer, Dordrecht (2008). Scholar
  19. 19.
    Vedder, A.: KDD: the challenge to individualism. Ethics Inf. Technol. 1, 275–281 (1999)CrossRefGoogle Scholar
  20. 20.
    Hildebrandt, M., Koops, E.J.: The challenges of ambient law and legal protection in the profiling era. Modern Law Rev. 73(3), 428–460 (2010)CrossRefGoogle Scholar
  21. 21.
    Leese, M.: The new profiling: algorithms, black boxes, and the failure of anti-discriminatory safeguards in the European Union’. Secur. Dialogue 45(5), 494–511 (2014)CrossRefGoogle Scholar
  22. 22.
    Mittelstadt, B.D., et al.: The ethics of algorithms: mapping the debate. Big Data Soc. 3, 1–21 (2016)CrossRefGoogle Scholar
  23. 23.
    van der Leun, J.P., van der Woude, M.A.H.: Ethnic profiling in The Netherlands? a reflection on expanding preventive powers, ethnic profiling and a changing social and political context. Policing Soc. 21(4), 444–455 (2013). Open Society Initiative (2013) Equality under Pressure: The Impact of Ethnic Profiling
  24. 24.
    Schermer, B.: The limits of privacy in automated profiling and data mining. Comput. Law Secur. Rev. 27, 45–52 (2011)CrossRefGoogle Scholar
  25. 25.
    Centrale Raad van Beroep: 21 November 2017, ECLI:NL:CRVB:2017:4068Google Scholar
  26. 26.
    Taylor, L., Floridi, L., van der Sloot, B. (eds.): Group Privacy: New Challenges of Data Technologies. Springer, Heidelberg (2017)Google Scholar
  27. 27.
    Mantelero, A.: Personal data for decisional purposes in the age of analytics: from an individual to a collective dimension of data protection. Comput. Law Secur. Rev. 32(2), 238–255 (2016)CrossRefGoogle Scholar
  28. 28.
    Birkinshaw, P.J.: Freedom of information and openness: fundamental human rights. Adm. Law Rev. 58(1), 177–218 (2006)Google Scholar
  29. 29.
    Larsson, T.: How open can a government be? The swedish experience’. In: Deckmyn, V., Thomson, I. (eds.) Openness and Transparency in the European Union. European Institute of Public Administration, Maastricht (1998)Google Scholar
  30. 30.
    Convention for the Protection of Individuals with regard to Automatic Processing of Personal Data (ETS No. 108, 28.01.1981)Google Scholar
  31. 31.
    De Hert, P., Papakonstantinou, V.: The police and criminal justice data protection directive: comment and analysis. Comput. Law Mag. SCL 2012 22(6), 1–5 (2012)Google Scholar
  32. 32.
    Council Framework Decision 2008/977/JHA of 27 November 2008 on the protection of personal data processed in the framework of police and judicial cooperation in criminal matters, L 350/60Google Scholar
  33. 33.
    Marquenie, T.: The police and criminal justice authorities directive: data protection standards and impact on the legal framework. Comput. Law Secur. Rev. 33, 324–340 (2017)CrossRefGoogle Scholar
  34. 34.
    Zarsky, T.: Transparent predictions. Univ. Ill. Law Rev. 4, 1503 (2013)Google Scholar
  35. 35.
    Annany, M., Crawford, K.: Seeing without knowing: limitations of the transparency ideal and its application to algorithmic accountability. New Med. Soc. 20(3), 973–989 (2018)CrossRefGoogle Scholar
  36. 36.
    Commissie modernisering opsporingsonderzoek in het digitale tijdperk, Regulering van opsporingsbevoegdheden in een digitale omgeving, June 2018.—regulering-van-opsporingsbevoegdheden-in-een-digitale-omgeving. This Committee, that reviewed Dutch criminal law in the light of digital developments, also concluded that an explicit requirement for explaining automated data analysis is necessary in national criminal procedural law
  37. 37.
    Cummings, M.L.: Automation bias in intelligent time critical decision support systems. In: AIAA 3rd Intelligent Systems Conference (2004)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Tilburg Institute for Law, Technology, and Society (TILT)Tilburg UniversityTilburgThe Netherlands

Personalised recommendations