The most widely read magazine for Canadian lawyers
Issue link: https://digital.canadianlawyermag.com/i/51655
BY DERA J. NEVIN TECH SUPPORT What is predictive coding and can it help me? I n large civil litigation and regulatory cases, the discovery process is becoming increas- ingly automated, scientific, and objective. This is evident by the increasing use of "predictive coding." Predictive coding are the new e-discovery buzzwords. Articles about the benefits of predictive coding have appeared in Forbes magazine and The New York Times. In mid-2011, one com- pany announced a patent for the tech- nology, sparking a war of words in the e-discovery press. Let's start with what predictive coding is not. It is not the "eyes on every docu- ment" approach of traditional linear review, where a lawyer starts with the first document and looks at every col- lected document until every document is reviewed. That approach works well when there is a small amount of docu- ments or in circumstances that require human eyes on every page. However, that approach becomes unwieldy and expensive when hundreds of thousands or millions of pages require review. Predictive coding remains poorly understood because it is not just a tech- nology but also a project management technique. Predictive coding is a series of computer search and sampling tech- nologies, coupled with a new approach to searching for and reviewing pot- entially responsive documents. Prop- erly combining all of these elements permits expedited, cost-effective, and highly accurate document review. Law- yers who use predictive coding need to understand how to combine these ele- ments. It's not necessarily the technolo- gies that are indefensible — just certain uses of them. Judges need to learn to recognize when their use has been or will be ineffective. Predictive coding has been described as lawyer-driven, computer-assisted document review. At its most basic, it review; but is a form of automated document strictly understanding it this way is to misapprehend the role predictive coding technology plays in searching for and retrieving potentially relevant documents. Predictive coding groups and organizes potentially rel- evant documents in a way that permits pass through another search iteration, or as many iterations as desired. As the computer learns to distinguish what is relevant, each iteration produces a smaller relevant subset, and a larger set of irrelevant documents that can be used to verify the integrity of the results, by confirming the absence of any rel- evant material through techniques such as sampling. The extent of the end use of the relevant set depends on the risk threshold of the clients and lawyers. Different predictive coding tools Predictive coding remains poorly understood because it is not just a technology but also a project management technique. human reviewers to maximize their review time and look at potentially related matters together. I prefer to think of predictive coding not as review technologies, but as search retrieval and information organization technologies applied to the discovery review process. Usually when predictive coding is described, lawyers who are intimately familiar with the case specify relevant criteria within small sets of data that define the crux of the issues. Lawyers generally do this through keywords or key concepts, but this can also be accomplished by reviewing a small set of documents to "train" the computer on the key issues. Through an iterative search process, computer algorithms retrieve a set of documents based on the criteria input by the lawyers. The reviewing lawyers may determine that some results are not relevant and request that the algorithm 24 JAN UARY 2012 www. CANADIAN Lawyermag.com use different algorithms and comput- ing techniques to obtain the smaller set of documents, but the effect of the technology is generally the same: a weighted ranking of documents accord- ing to likely relevance as established by the lawyer. Predictive coding is generally defined by these characteristics: • it leverages small samples of docu- ments (input criteria) to find other relevant documents; • it reduces the number of non-relevant documents that lawyers must review, thereby reducing the overall amount of lawyer time spent reviewing docu- ments; and • unlike straight manual review of docu- ments by lawyers, the results generated by predictive coding algorithms can be validated through statistics. The use of predictive coding for document review raises at least two