There has recently been talk of algorithms that predict decisions in legal cases being used by the judiciary to improve the predictability and consistency of judicial decision making. We argue that their use may minimise the error rate of decisions in the long run, but that this would require not only major technical advances but also major changes in legal thinking about what is the most important objective of judicial decision-making: optimising individual justice in a particular case or reducing errors in the long run. We further argue that if algorithmic decision predictors give any useful information in individual cases to judges at all, this is not in its predictions but in its explanations.
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