Last month Magistrate Judge Andrew Peck, of the U.S. District Court for the Southern District of New York, issued an opinion in a gender discrimination case that had this to say about computer-assisted review: “Computer-assisted review is an available tool and should be seriously considered for use in large-data-volume cases where it may save the producing party (or both parties) significant amounts of legal fees in document review.”

In doing so, he just also may have made a case for the legal profession to do some more investigation of semantic technology in order to cope with its own Big Data challenges. In the mid-2000s, the Federal Rules of Civil Procedure were amended to take into account electronic discovery, so that both sides in a legal challenge would have to confer within sixty days of filing to disclose how they handled digital data. The beauty of the American legal system is that it requires each party to pony up information that is meaningful and responsive to the facts of the case. The dark side is that the proliferation of data inside businesses means employees are creating more and more data in lots of different ways, which means legal staff has to spend a lot more time sifting through digital realms of structured and unstructured information to discover what may have to do with a lawsuit or government investigation, what is responsive to the other party’s document request, and what is privileged information, too.

“It’s created a cottage industry in temp staffing – now there are temp lawyers, contract attorneys who work from $30 to $75 an hour,” says Jay Leib, Chief Strategy Officer at kCura, which makes the Relativity Assisted Review e-discovery text analytics software based on latent semantic indexing technology. “Just like we outsource factory workers, there are outsourced attorneys overseas doing document review to combat the amount of data that’s sprung up.” There is so much data out there that it’s entirely possible that a $3 million lawsuit could cost $6 million to litigate, he says.

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