Algorithms and Regulation

Technological progress could constitute a huge benefit for law enforcement: greater efficiency, effectiveness and speed of operations as well as more precise risk analyses, including the discovery of unexpected correlations, which could feed nourish profiles. A number of new tools entail new scenarios for information gathering, as well as the monitoring, profiling and prediction of individual behaviours, thus allegedly facilitating crime prevention: algorithms, artificial intelligence, machine learning and data mining. Law enforcement authorities have already embraced the assumed benefits of big data. However, there is a great need for an in-depth debate about the appropriateness of using algorithms in machine-learning techniques in criminal justice, assessing how the substance of legal protection may be weakened. Given that big data, automation and artificial intelligence remain largely under-regulated, the extent to which data-driven surveillance societies could erode core criminal law principles such as reasonable suspicion and the presumption of innocence, ultimately depends on the design of the surveillance infrastructures. This contribution first addresses the so-called rise of the algorithmic society and the use of automated technologies in criminal justice to assess whether and how the gathering, analysis and deployment of big data are changing law enforcement activities. It then examines the actual or potential transformation of core principles of criminal law and whether the substance of legal protection may be weakened in a ‘data-driven society’.