E-discovery seismic shifts have become so common that we are often quick to forget what we haven’t yet learned.
What I mean is that the e-discovery technical revolution throws so many new tools at us that we can fixate on them before we have fully understood and adopted previous, effective process improvements. Keyword searching is a classic example. With all the rush to the varieties of “predictive coding,” “computer assisted review” and machine learning, we have failed to get keyword searching right before promptly bidding it an abrupt “adieu.”
How did we make keyword searches better? The answer is multifaceted. Some efficacious solutions had already been deployed before we became transfixed, ogling the new big thing. For example, Boolean searching has been available to help exclude misidentified documents, while “near” and “within” search capabilities have helped capture phrases. There’s also fuzzy logic already at your disposal to help identify misspelling, and stemming to catch words with the same core. In short, keyword search has been there, nicely functioning as an iterative process of refinement rather than a one-shot game of good guessing. Search terms have evolved into developed “search strings” and “search expressions.” Help was on the way and had arrived.
But before we mastered all of these utilities, predictive coding arrived on the heels of some interesting studies, which suggested that even though we thought keyword practice was improving, we still had a long way to go to beat the latest machine-learning algorithms. After all, “Watson” won at Jeopardy. In a flash, the e-discovery world was chasing the new “predictive coding” technologies as if they were robo-heroes and keyword searching a limping dinosaur. Don’t get me wrong! These are wonderfully powerful technologies that have been increasingly deployed in significant cases, and they promise even more excitement for the everyday case in the near future. But they are only a few technologies in the big e-discovery toolbox, shiny and new as they may be.