For nearly as long as computers have existed, litigators have used software-generated machine output to buttress their cases, and courts have had to manage a host of machine-related evidentiary issues, including deciding whether a machine’s output, or testimony based on the output, could fairly be admitted as evidence and to what extent. Today, as litigants begin contesting cases involving aspects of so-called intelligent machines–hardware/software systems endowed with machine learning algorithms and other artificial intelligence-based models–their lawyers and the judges overseeing their cases may need to rely on highly-nuanced discovery strategies aimed at gaining insight into the nature of those algorithms,…