3 steps to becoming a "predictive coding guru"
National Public Radio recently said that predictive coding could let "one attorney do the work of 500."
June 18, 2012 at 04:30 AM
12 minute read
The original version of this story was published on Law.com
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.
Predictive coding is a type of machine learning technology that enables a computer to automatically predict how documents should be classified based on a limited, but significant, level of human input. The technology is exciting for legal departments attempting to manage skyrocketing litigation budgets because the ability to automatically rank and then “code” or “tag” electronic documents based on criteria such as relevance and privilege has the potential to save companies millions in e-discovery costs.
The potential cost savings of predictive coding technology are so great that corporate legal departments inevitably will expect the law firms that represent them to learn how to use the technology. Much like the shift from paper to electronic file conversion was driven by the potential for cost savings, so too is the buzz surrounding predictive coding technology.
While the days of “brute force,” linear document review are rapidly disappearing, the role of savvy e-discovery practitioners is still vital, and predictive coding provides a land of opportunity for those eager to capitalize on the trend. The emerging body of case law (Da Silva Moore, Kleen Products and Global Aerospace) shows that there is no shortage of work required to negotiate and craft protocols for the use of this new technology, even before the review process begins.
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.
For a simpler approach to reaching “predictive coding guru” status start with these three basic steps:
1. Read up on the topic
There is a tremendous amount of information available on the Internet that covers everything from predictive coding 101 to recent case law. Reading articles from trusted sources will help you understand predictive coding at a high level, particularly surrounding the role of inside/outside counsel.
These resources provide a good primer:
- “Search, Forward: Will manual document review and keyword searches be replaced by computer assisted-coding?”
- “2012: Year of the Dragon – and Predictive Coding? Will the eDiscovery Landscape Be Forever Changed?”
- “Technology-Assisted Review in Electronic Discovery Can Be More Efficient And More Cost Effective Than Exhaustive Manual Review”
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.
The good news is that independent industry analysts like Gartner prepare several reports annually that evaluate e-discovery market trends, so there's no need to start from scratch. Gartner's 2012 “Magic Quadrant for E-Discovery Software” report is a particularly good starting point for understanding current e-discovery trends like predictive coding, as well as the major players in the broader e-discovery and information governance space.
3. Test drive the software
The next step for gathering information about predictive coding technology should include observing live product demonstrations. Specific things to look for in any predictive coding product include transparency and ease of use for end users, recommended workflow, chain of custody reporting and broader integration with other important e-discovery modules. Finally, be wary of e-discovery providers suggesting that predictive coding technology tools will replace all other e-discovery technologies. Providers belittling the broader e-discovery and information governance picture probably don't offer much beyond predictive coding technology, so they may try to focus the conversation exclusively on document review and analysis.
Other valuable steps in the e-discovery process that must be accounted for (in addition to document review) include proactively establishing an internal records retention schedule, legal hold notification, data identification and collection, early case assessment and data filtering.
Conclusion
For some outside law firms and contract attorney service bureaus, it's been all too easy to become addicted to the high utilization associated with e-discovery document review projects. But, for inside counsel, those massive numbers of e-discovery hours have become an easy target, at which the latest predictive coding technology is squarely aimed.
And yet, the demise of attorneys in the review process has been vastly overstated. Savvy legal professionals interested in advancing their careers and being on the cutting edge of something new will invest time in understanding the future of predictive coding or risk becoming less relevant.
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.
Predictive coding is a type of machine learning technology that enables a computer to automatically predict how documents should be classified based on a limited, but significant, level of human input. The technology is exciting for legal departments attempting to manage skyrocketing litigation budgets because the ability to automatically rank and then “code” or “tag” electronic documents based on criteria such as relevance and privilege has the potential to save companies millions in e-discovery costs.
The potential cost savings of predictive coding technology are so great that corporate legal departments inevitably will expect the law firms that represent them to learn how to use the technology. Much like the shift from paper to electronic file conversion was driven by the potential for cost savings, so too is the buzz surrounding predictive coding technology.
While the days of “brute force,” linear document review are rapidly disappearing, the role of savvy e-discovery practitioners is still vital, and predictive coding provides a land of opportunity for those eager to capitalize on the trend. The emerging body of case law (Da Silva Moore, Kleen Products and Global Aerospace) shows that there is no shortage of work required to negotiate and craft protocols for the use of this new technology, even before the review process begins.
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.
For a simpler approach to reaching “predictive coding guru” status start with these three basic steps:
1. Read up on the topic
There is a tremendous amount of information available on the Internet that covers everything from predictive coding 101 to recent case law. Reading articles from trusted sources will help you understand predictive coding at a high level, particularly surrounding the role of inside/outside counsel.
These resources provide a good primer:
- “Search, Forward: Will manual document review and keyword searches be replaced by computer assisted-coding?”
- “2012: Year of the Dragon – and Predictive Coding? Will the eDiscovery Landscape Be Forever Changed?”
- “Technology-Assisted Review in Electronic Discovery Can Be More Efficient And More Cost Effective Than Exhaustive Manual Review”
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.
The good news is that independent industry analysts like
3. Test drive the software
The next step for gathering information about predictive coding technology should include observing live product demonstrations. Specific things to look for in any predictive coding product include transparency and ease of use for end users, recommended workflow, chain of custody reporting and broader integration with other important e-discovery modules. Finally, be wary of e-discovery providers suggesting that predictive coding technology tools will replace all other e-discovery technologies. Providers belittling the broader e-discovery and information governance picture probably don't offer much beyond predictive coding technology, so they may try to focus the conversation exclusively on document review and analysis.
Other valuable steps in the e-discovery process that must be accounted for (in addition to document review) include proactively establishing an internal records retention schedule, legal hold notification, data identification and collection, early case assessment and data filtering.
Conclusion
For some outside law firms and contract attorney service bureaus, it's been all too easy to become addicted to the high utilization associated with e-discovery document review projects. But, for inside counsel, those massive numbers of e-discovery hours have become an easy target, at which the latest predictive coding technology is squarely aimed.
And yet, the demise of attorneys in the review process has been vastly overstated. Savvy legal professionals interested in advancing their careers and being on the cutting edge of something new will invest time in understanding the future of predictive coding or risk becoming less relevant.
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