Prediction, Persuasion, and the Jurisprudence of Behaviorism
19 Pages Posted: 10 Nov 2017
Date Written: November 8, 2017
Machine learning experts are feeding judicial opinions to algorithms, to predict how future cases will be decided. We call the use of such predictive analytics in judicial contexts a jurisprudence of behaviorism, as it rests on a fundamentally Skinnerian model of cognition as a black boxed transformation of inputs into outputs. In this model, persuasion is passé; what matters is prediction. After describing and critiquing a recent study that has advanced this jurisprudence of behaviorism, we question the value of such research.
Keywords: Black Box Algorithms, Judicial Decisions, Predictive Analytics, Natural Language Processing, Machine Learning, Legal Realism, N-Grams, Spurious Correlations
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