This chapter explores the legal and moral implications of the use of data science in criminal justice at two levels: police surveillance and the criminal trial of a defendant. At the first level, police surveillance, data science is used to identify places and people at high risk of criminal activity, allowing police officers to target surveillance and take proactive measures to try to prevent crime (predictive policing). At the second level, the criminal trial of a defendant, data science is used to make risk assessments to support decisions about bail, sentencing, probation, and supervision and detention orders for high-risk offenders. The use of data science at these levels has one thing in common: it is about predicting risk. The uncertainty associated with risk prediction raises specific related legal and ethical dilemmas, for example in the areas of reasonable suspicion, presumption of innocence, privacy, and the principle of non-discrimination.
Producing evidence that can be used in court is a central goal of criminal investigations. Forensic science focuses with considerable success on the production of pieces of evidence from specific sources. However, less is known about how a team of investigating police officers progressively produces a body of evidence during the course of a criminal investigation. This literature review uses Weickian sensemaking to analyse what is known about this process in criminal investigations into organised crime. Focusing on the criminal investigation team, collective sensemaking is used as a lens through which to place the reasoning processes used in constructing evidence in a social context. In addition to describing three constituent parts of collective sensemaking relevant for criminal investigations, six factors are identified that influence the quality of collective sensemaking. Building on these results, nine focal points are presented for analysing the sensemaking processes in a criminal investigation team, aimed at advancing knowledge about the production of evidence in criminal investigations of organised crime. Furthermore, a definition of evidence is developed that is suitable for studying sensemaking in the context of an ongoing criminal investigation.
In this article, the author will question the seemingly obvious boundary between civil disobedience, as conceptualised by Rawls and Arendt, and several examples of criminal, or simply annoying, activities which don't meet their criteria, such as the case of the ‘Top 50'. The ‘Top 50' are multi-problem Dutch-Caribbean men, who refuse to adapt to predominant norms in Dutch society. IThe author argues that political aspects of their behaviour should be acknowledged, even if they engage in criminal behaviour and don't present explicit political goals. Firstly, she questions the way in which Rawls based his definition on a centralistic conception of governmental power and contrast it with Foucault's conception of normalising power, in which power is diffuse and cannot be restricted to the enactment of formal laws. Secondly, she discusses what the minimum requirements are to be able to classifyacts as civil disobedience. Rawls and Arendt draw a clear line between criminal behaviour and civil disobedience, but their requirements may be too strict. We might miss signals of injustice if actions that do not meet these criteria are excluded from the political discourse. The conclusion is that comparing Arendt's and Rawls' conception of civil disobedience with the behaviour of a marginal migrant group may be useful in questioning the boundaries of this concept and in making it more inclusive. A wider conception of civil disobedience may help to explain the meaning of deviant behaviour in terms of social critique and to challenge the traditional understanding of civil disobedience.
