National Public Radio recently said that predictive coding could let "one attorney do the work of 500." Despite the apparent hyperbole, it’s still easy to get excited about new technological advances. Perhaps more important, though, is to divine what this tectonic shift might mean for practicing attorneys in reality. Several questions naturally arise, including what will the face of document review look like over the next decade, and how will this new landscape affect the practice of law?
More than a decade ago, even before electronic discovery became mainstream, many in the legal field saw another development underway: a gradual shift away from using hard copy documents for managing discovery toward converting those same documents into electronic images. The trend developed because converting paper documents to searchable image files with scanning and optical character recognition software was simply far more cost-efficient and manageable than dealing with paper. While this paradigm shift dramatically impacted the litigation playing field, it didn’t threaten to steal billable hours like the type of automation seen on the horizon with new technology like predictive coding.
After protocols for sampling and training are sorted out, there’s still a need for skilled attorney reviewers (likely billing at higher hourly rates) to tag and code documents so the system can be accurately trained. Similarly, the role of attorneys in evaluating the quality of the computer’s decisions is increasingly important since most believe that the documents designated as highly relevant by the computer should undergo a final human review prior to production.
In order to capitalize on new technology trends like predictive coding, though, it’s important to embrace the new changes instead of taking an ostrich approach. While the task might seem daunting, the complexity surrounding early predictive coding tools has created an opportunity to learn a new method that many less-enterprising practitioners may foolishly pass up. That means the area is still ripe with opportunity—and the good news is that becoming an organization’s go-to person for predictive coding does not necessarily require obtaining an advanced degree in statistics or computer science.
2. Understand the market dynamics and tools
The predictive coding software market is flooded with numerous companies claiming to provide “leading” predictive coding solutions. The challenge with any burgeoning market is to separate the players from the poseurs.