by Tony Rushin
Predictive coding, aka computer-assisted review, is an evolving technology that provides litigants an alternative to the time and cost of manual review of large document sets. Attorneys select a sample set, or “seed set,” of relevant and irrelevant documents, which are then coded as the baseline for the automated collection and review of documents. Using the sample set, the computer is able to quite literally learn what the criteria for relevance and irrelevance are, and automatically review data based on that knowledge.
Within the last month, The U.S. District Court for the Southern District of New York in Da Silva Moore v. Publicis Groupe, Case No. 1:11-cv-01279 (S.D.N.Y. April 26, 2012), and the Circuit Court for Loudon County, Va., in Global Aerospace v. Landow Aviation, Case No. CL 61040 (Va. Cir. Ct. Loudon Co. April 23, 2012), have endorsed the use of predictive coding as a viable and economical alternative to the traditional method of keyword searching and manual review of documents.
Also of note is Kleen Products v. Packaging Corporation of America, Case No. 10 C 5711 (N.D. Ill.), a case pending in the U.S. District Court for the Northern District of Illinois. Recent transcripts reveal that 7th Circuit Magistrate Judge Nan Nolan has urged the parties to focus on developing a mutually agreeable keyword search strategy for eDiscovery instead of debating whether other search and review methodologies would yield better results.
The use of predictive coding or other new technology — particularly as it is refined, tested, and improved — offers litigators the chance to focus on the preparation of their cases, young lawyers can be trained in useful skills, and cases can be resolved on merits rather than cost considerations. The recent decisions in Da Silva Moore and Global Aerospace suggest that legal practitioners should consider the pros and cons of using new e-discovery technology in their own cases, as it appears that predictive coding is gaining acceptance.
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