Predictive judicial analytics holds the promise of increasing efficiency and fairness of law. Judicial analytics can assess extra-legal factors that influence decisions. Behavioral anomalies in judicial decision-making offer an intuitive understanding of feature relevance, which can then be used for debiasing the law. A conceptual distinction between inter-judge disparities in predictions and inter-judge disparities in prediction accuracy suggests another normatively relevant criterion with regards to fairness. Predictive analytics can also be used in the first step of causal inference, where the (...) features employed in the first step are exogenous to the case. Machine learning thus offers an approach to assess bias in the law and evaluate theories about the potential consequences of legal change. (shrink)

Into Jeffrey Tulis’s argument that “the rhetorical presidency signals and constitutes a fundamental transformation of American politics” he inserts parenthetically the question, “Has the rhetorical presidency now given birth to the rhetorical judiciary?” Whether the rhetorical presidency birthed or simply predated the rhetorical judiciary is open to question. The existence of the rhetorical judiciary is not. Since the publication of The Rhetorical Presidency, judges and their interlocutors have ratified one of the insights that grounded Tulis’s question, while challenging another. They (...) have borne out his fear that judges would increasingly respond to attack; his worry about the vacuity of confirmation hearings for those nominated to the Supreme Court, however, has not been similarly confirmed. (shrink)