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Profiling ‘Anomalies’ and the Anomalies of Profiling: Digitalized Risk Assessments of Dutch Youth and the New European Data Protection Regime

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Abstract

A key component of the proposed data protection rules outlined in the General Data Protection Regulation (GDPR ) is that any measures based solely on automated data processing that have legal effects on ‘natural persons’, including children, count as ‘profiling ’. Currently, the digitalized profiling of children in Dutch child-care policies has gradually gained prominence in efforts to detect or prevent child abuse and anti-social or delinquent behaviour. This chapter analyses how the proposed data protection rules will impact the current practices of profiling children and creating individualized risk assessments in the Netherlands. To illustrate the problems raised by such profiling, this paper analyses the professional use of three profiling registries: the Dutch Digital Youth Healthcare Registry , the Reference Index of High-Risk Youth , and the ProKid SI 12-system. Investigating the negative implications of the use of these and determining how these implications can be addressed by legal means is crucial to striking a proper balance between the interests of society, privacy and data protection, and individual children and families. Although each registry is meant to prevent problems and serve the ‘best interests’ of children and society, their use produces new risks, including the possibility for erroneous criminal prognosis, stigmatization, and discrimination. By drawing upon empirical data and legal analysis, this paper argues that the use of these technologies by authorities and healthcare providers in the Netherlands will challenge new data protection provisions and that it is therefore necessary to reframe the data protection regime to better protect “the best interest of the child” as established by the United Nations Convention on the Rights of the Child.

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Notes

  1. 1.

    By children, I mean in this article all persons between 0 and 23 years. This is a practical choice. I simply followed the definition used by the Reference Index High-Risk Youth, which uses the broadest age definition for a child among the three systems analysed here. Therefore, by this term I mean children assessed by any of the three systems.

  2. 2.

    The Minister of Youth and Family: André Rouvoet explained in an interview (Van Wijck 2009), that during his 13 year carrier being an MP he experienced no discussion on the topic of child abuse, therefore how glad he was that the topic was finally put on the top of political agendas.

  3. 3.

    Wet Bescherming Persoonsgegevens 2000 (Data Protection Act) Retrieved on 10th August 2014, from <http://wetten.overheid.nl/BWBR0011468>.

  4. 4.

    Controversies around these systems also provide reasons for thorough analysis. For instance, the Dutch government’s ability to safeguard transparency and the proper protection of personal data had already been raised as focal points for investigation in light of such IDM systems (Klingenberg and Lindeboom 2013). These issues raise further controversies as to how to orchestrate legally, administratively and technically the preventive profiling of children in each of these sectors. Controversies also surround the vividly disputed potential negative implications the transition in the youth care and law enforcement sector might cause, as well as the government’s increasing push to exchange data (Goedee and Rijkers 2010) across sectors.

  5. 5.

    As of January 2015 Bureau Youthcare organizations are abolished and their tasks are taken over by other certified youth care organizations and the municipalities.

  6. 6.

    As of January 2015 Bureau Youthcare organizations do not exist in their old form anymore in The Netherlands. Due to the decentralization process in youth care, the tasks earlier performed by Bureau Youthcare had been redivided and redistributed between newly certified youth care organizations and city halls.

  7. 7.

    Despite a newly emerging trend where online profiling gains importance, the risk profiling of children by Dutch government technologies such as the Digital Youth Healthcare Registry, the Reference Index High Risk Youth and the ProKid 12–SI system occur against an already defined set of criteria, and those criteria should be set by standards in healthcare, youth care or law enforcement in The Netherlands. Each match between a profile and a child is regularly nominative and shows that a child is associated by name to a risk category.

  8. 8.

    Elektronisch Kinddossier eind 2010 ingevoerd <http://webwereld.nl/beveiliging/42055-elektronisch-kinddossier-eind-2010-ingevoerd#>.

  9. 9.

    Each category definition emerges as natural or innocent to the person it characterizes, yet when personal attributes captured within categories become benchmarks upon which decisions of exclusion or inclusion are made, the BDS categories can also be seen as ‘carriers’ of certain selective politics.

  10. 10.

    For more information about this, please see: <http://knmg.artsennet.nl/Nieuws/Overzicht-nieuws/Nieuwsbericht/39762/KNMG-Elektronisch-Kinddossier-niet-te-breed-toegankelijk-maken.htm>.

  11. 11.

    Minister van Veiligheid en Justitie (2012), 29 279 Rechtsstaat en Rechtsorde Nr. 147 Brief van de minister van veiligheid en justitie aan de Voorzitter van de Tweede Kamer der Staten-Generaal, Den Haag.

  12. 12.

    Brief van de Staatssecretaris van Veiligheid en Justitie over het ‘EU-voorstel: Richtlijn bescherming persoonsgegevens bij gebruik door politiële en justitiële autoriteiten (COM(2012)10) en EU-voorstel Verordening algemeen kader bescherming persoonsgegevens (COM(2012)11)’ (2013).

  13. 13.

    Part of the empirical data in this article can also be found in La Fors-Owczynik and Valkenburg (2015). Part of empirical data concerning ProKid can also be found in La Fors-Owczynik (2015).

  14. 14.

    For this prescription, see ECJ, Luxembourg, 13 May 2014, C-131/12.

  15. 15.

    Here, the word construction certainly does not intend to suggest that risks are made up of thin air, but the risks within the administration of professionals become existent, noticeable and actionable for others through their digital registration.

  16. 16.

    The financial steering of risk registration in the Reference Index High-Risk Youth is not a nationwide phenomenon, but it depends on the choices local governments make.

  17. 17.

    Certainly, this observation only applies to the specific city where the interviewee coordinated and managed the registration of risk signals by all partner organizations linked to the system.

  18. 18.

    In the Netherlands, municipalities maintain the addresses of all their inhabitants through central registries.

  19. 19.

    This phenomenon has been raised as a problem by 2/3 of the interviewed youth healthcare professionals.

  20. 20.

    About further descriptions of colour codes in ProKid please see: Abraham et al. (2011, DSP-groep).

  21. 21.

    In 2007 to facilitate collaboration between the Dutch police and Bureau Youthcare, a flagship organization within Dutch youth care, which collaboration also forms the basis for ProKid: “Early identification and referral” policy had been introduced. About this, see more in: Goedee and Rijkers (2010, Ministerie van Jeugd en Gezin).

  22. 22.

    The interviews that provided empirical material for this article were conducted before 2015. As of January 2015, as a consequence of the administrative reorganization of Dutch youth care Bureau Youthcare organizations do not exist anymore, but their tasks are redistributed to municipalities and newly certified agencies of youth care. The police share its concerns in relation to children with other parties according to the new set-up of the organizations in charge of youth care.

  23. 23.

    As the interviews demonstrated drawing random correlations in ProKid is possible, because the technological settings allow for a rather horizontal—information visible on more children—view of children and because the system promotes professionals to take up digitally depicted issues which they see as providing better prevention.

  24. 24.

    The Basic Facility for Forensic Investigation (BFFI, or Basisvoorziening Opsporing in Dutch) is a law enforcement database of the Dutch police, where a variety of observations of police officers are registered.

  25. 25.

    See about this the Individual Healthcare Professions Act (Wet op de beroepen in de individuele gezondheidszorg, 1993) which entails confidentiality requirements for professionals about how to share patients’ data, or the Act on Medical Treatment Contacts Act (Wet Geneeskundige Behandelingsovereenkomst, 1994) which entails prescriptions about accessing patients’ files.

  26. 26.

    DOSA organisations have a helicopter view of youth care related organizations and professionals and are notified about each risk signal and match registered in RI. DOSA professionals are not responsible for solving cases but for only assisting other professionals in solving them.

  27. 27.

    Recital 29 of the General Data Protection Regulation of the European Union (15 December 2015).

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Acknowledgments

The research which enabled this chapter had been funded via the DigIDeas project, which was granted to Dr. Irma van der Ploeg by the European Research Council under the European Union’s Seven Framework Programme (FP7 2007–2013)/Grant No. 201853/. Furthermore, I am very grateful to Prof. Corien Prins for her support and insightful comments on this chapter.

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La Fors-Owczynik, K. (2017). Profiling ‘Anomalies’ and the Anomalies of Profiling: Digitalized Risk Assessments of Dutch Youth and the New European Data Protection Regime. In: Adams, S., Purtova, N., Leenes, R. (eds) Under Observation: The Interplay Between eHealth and Surveillance. Law, Governance and Technology Series(), vol 35. Springer, Cham. https://doi.org/10.1007/978-3-319-48342-9_7

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