There have been two important decisions within the last month concerning courts’ acceptance of a new technology that may help reduce the costs associated with, and increase the efficiency of, processing and reviewing electronically stored information (ESI) in e-discovery. The technology, known as “predictive coding,” allows attorneys to 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 seed 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, thereby potentially eliminating a significant portion of the burden and costs associated with the process of having attorneys perform the initial first-tier reviewthe stage at which the majority of wasteful e-discovery costs are incurred.1
As discussed below, 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.
This content has been archived. It is available through our partners, LexisNexis® and Bloomberg Law.
To view this content, please continue to their sites.
Not a Lexis Subscriber?
Subscribe Now
Not a Bloomberg Law Subscriber?
Subscribe Now
LexisNexis® and Bloomberg Law are third party online distributors of the broad collection of current and archived versions of ALM's legal news publications. LexisNexis® and Bloomberg Law customers are able to access and use ALM's content, including content from the National Law Journal, The American Lawyer, Legaltech News, The New York Law Journal, and Corporate Counsel, as well as other sources of legal information.
For questions call 1-877-256-2472 or contact us at [email protected]
