Plaintiff Programmatic Issue Coding: The Scalpel of Document Review Tools
Anyone who keeps up with eDiscovery rules and law knows that a district court has affirmed U.S. Magistrate Judge Andrew J. Peck’s judicial order in Monique Da Silva Moore v. MSL Group, No. 11 Civ. 1279 (ALC)(AJP) (S.D.N.Y. 2012). In the case, Magistrate Judge Peck pronounced, “Computer assisted review is an acceptable way to search for ESI in appropriate cases.” The order was the first legal opinion in the country to affirm the use of computer assisted review to find responsive documents, although in the case the judge allowed the defense to predictively code its internal documents before producing the data to plaintiffs.
Although Judge Peck was correct that predictive coding should be used in complex litigation, plaintiffs’ counsel can obtain the entire defense production and issue code the data themselves. Issue coding works by having a team of subject matter experts code a small “seed” set of documents to determine the language analytics for the search. Once the seed set of documents are approved by human review, the computer will continue issue coding on its own.
While corporations and defendants use predictive issue coding internally to better understand their own ESI, this type of broad and generalized coding is the equivalent of using a hack saw to find generally responsive documents to the RFPs. On the other hand, enhanced plaintiff Programmatic Issue Coding is a scalpel. Programmatic issue coding uses artificial-intelligence based language analytics that does more than just find broad topics; the computer actually “thinks” like a human to pinpoint documents related to specific issues and scoring these documents for each issue with unbeatable accuracy.
ESI productions will continue to grow and Programmatic Issue coding is here to stay. Accuracy is of the utmost importance to any case involving analytics-based litigation issue coding. Call us at 888-313-4457 for further information about how our plaintiff eDiscovery software differs from and improves upon defendant-oriented issue coding.