Break up the Family: Protocols for Efficient Recall-Oriented Retrieval Under Legally-Necessitated Dual Constraints

摘要

In the legal domain, the primary objective of eDiscovery is to retrieve, from within a document population, as many individual relevant documents as possible given the expenditure of a reasonable review effort. The production of relevant documents to opposing counsel, however, is typically made on a family basis (an email and all its attachments), such that the entire family is produced as a collective unit. Counsel's ethical responsibility to prevent the disclosure of privileged information necessitates review of every document in every family being produced. Consequently, it is standard industry practice to batch entire families for review together. This work examines the overall review ordering and efficiency of alternative techniques for managing review leading to the production of relevant document families while fully protecting privilege. Batching, document sequencing, and therefore, training of the core supervised machine learning (AI) algorithm differ among each protocol, and lead to different overall efficiencies. Our empirical results support two conclusions. First, break up the family. In every instance, broken family retrieval protocols are more efficient than full family protocols. Second, a carefully designed and implemented dual phase workflow incorporating an initial, expedited relevance review can be more efficient than a single phase workflow, even if some documents are reviewed twice.