The Delayed Countdown Method for Validating Review-Oriented AI Workflows in eDiscovery
Review-oriented workflows have become the dominant approach to AI-assisted document review in electronic discovery (eDiscovery). How to validate the effectiveness of review-oriented workflows has, however, remained a confusing and controversial topic in technology-assisted review (TAR) in the law. We examine the sources of this controversy, and propose a simple and practical evaluation approach for review-oriented workflows. Our Delayed Countdown method is easily incorporated into existing review-oriented workflows and software, is compatible with arbitrary stopping rules, and produces valid frequentist confidence intervals on effectiveness. We explain the conceptual foundations of the method, provide example computations, discuss the handling of logically impossible recall values, and suggest future work on decreasing review costs.