![]() ![]() For instance, multiple areas of applied machine learning show how new methods of unsupervised learning or active learning operate in a way that avoids human intervention. Footnote 2 The intermediate phases in the process of reaching a decision are by definition hidden from human oversight due to the technical complexity involved. The technical sophistication of the new AI systems used in decision-making processes in criminal justice settings often leads to a ‘black box’ effect. The automation brought about by AI systems challenges us to take a step back and reconsider fundamental questions of criminal justice: What does the explanation of the grounds of a judgment mean? When is the process of adopting a judicial decision transparent? Who should be accountable for (semi-) automated decisions and how should responsibility be allocated within the chain of actors when the final decision is facilitated by the use of AI? What is a fair trial? And is the due process of law denied to the accused when AI systems are used at some stage of the criminal procedure? ![]() While authors disagree whether these technologies represent a panacea for criminal justice systems-for example by reducing case backlogs-or will further exacerbate social divisions and endanger fundamental liberties, the two camps nevertheless agree that such new technologies have important consequences for criminal justice systems. With the advent of big data analytics, machine learning and artificial intelligence systems (henceforth ‘AI systems’), Footnote 1 both the assessment of the risk of crime and the operation of criminal justice systems are becoming increasingly technologically sophisticated. ![]()
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