Inside the Black Box: A Practitioner’s Guide to Machine Learning Used in Pricing Algorithms

Though now a part of the modern vernacular, machine learning mechanisms that motivate algorithmic pricing remain “black box” terms to many antitrust practitioners and legal scholars alike. Such informational barriers impede proper evaluation of these pricing methodologies, potentially either failing to detect anticompetitive conduct or inadvertently condemning innocuous or even procompetitive practices. Determining the relative likelihood of either outcome requires, inter alia, a working und