What Tools & Technology Should a Litigator Have in Their Toolbelt?
Too often we hear the common refrain that lawyers are luddites–technologically challenged professionals who are unwilling to adopt modern techniques for practicing law. But, is this polarizing portrayal completely accurate?
Technology providers have made many great strides when it comes to electronic discovery, but too often their message is unheard outside the 1% of eDiscovery cognoscenti who attend every legal technology conference. For the other 99%, it is an acronym laden road to understanding how new technology can meet their electronic discovery needs.
Now, we don’t want to diminish the importance of all the new features that vendors have developed, but we need a simpler construct to help eDiscovery novices begin to make sense of all the new tools at their disposal.
To facilitate understanding of new search and review techniques, let’s take a spectrum of Human Interaction. On the far left we have carbon or human-based and on the far right we have silicon or computer-based. This critical distinction between whether a human is doing the majority of the work versus whether a computer is doing the work helps us to distinguish between resource requirements for these new technologies.
Overall, Technology-Assisted Review (TAR) is a process for prioritizing or coding documents using a computerized system. Predictive coding is one TAR technique that harnesses human judgments on a smaller set of documents and then extrapolates those judgments to the remaining document collection. Other approaches like discussion threading and clustering automatically extract patterns from the data and expose relationships between key people and documents in a chronological timeline with minimal human intervention.
This chart plots some different TAR techniques and their respective degrees of human interaction. To provide further clarity, here are some additional definitions for common TAR techniques:
• Keyword search: in its simplest form, a word is input into a computer system which then retrieves the documents within the collection that contain the same word. Keyword search tools typically include enhanced capabilities that leverage Boolean operators to identify word combinations and derivatives of root words.
• Concept search: typically involves the use of linguistic and statistical algorithms to determine whether a document is responsive to a particular keyword search query. The technology considers variables such as the proximity and frequency of words that appear in relationship to the keywords used.
• Predictive coding: a type of machine-learning technology that enables a computer to “predict” how documents should be classified based on input or “training” provided by human reviewers.
• Discussion threading: utilizes algorithms to dynamically link together related documents (most commonly e-mail messages) into chronological threads that reveal entire discussions.
• Clustering: involves the use of linguistic algorithms that automatically organize a large collection of documents into different topical groupings based on similarity.
• Find similar: enables the retrieval of documents related to a particular document of interest. Reviewing similar documents together can simplify the review process, provide broader context, and help increase coding accuracy.
• Near-duplicate identification: allows reviewers to easily identify, retrieve, and code documents that are very similar but not exact duplicates. Some systems can highlight discrepancies between near-duplicate documents which makes identifying subtle differences between documents easier.
It’s important to assuage the confusion in the market today that predictive coding renders other TAR tools obsolete. To the contrary, predictive coding technology should be viewed as one of many different tools in the Litigator’s Toolbelt™ that can and should be used independently or in any combination depending on the needs of the case. Understanding how predictive coding technology and other TAR tools can be used together as part of a defensible eDiscovery process can help organizations reduce risk and cost simultaneously. To learn more, download a free copy of Predictive Coding for Dummies.
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