Guest Post by Adam Wells
TERIS Vice President, Business Development & eDiscovery Services
There’s no disputing that Assisted Review (AR) is recognized as an acceptable (read: defensible) method for streamlining both the time and expense encountered during ESI review. AR advocates can be found across the spectrum – both defense attorneys and plaintiff attorneys have begun to eschew traditional linear review for a model that relies on the intelligent application of advanced technologies. Indeed, three venerable plaintiff attorneys (a group that, at least by reputation, tends to view AR with some skepticism) recently extolled the virtues of AR in an excellent piece for LTN (Technology Assisted Review from the Plaintiffs’ Side). To be sure, these attorneys (Ariana Tadler, Paul McVoy, and Henry Kelston) expressed an element of skepticism in all the right places, insisting that AR should not completely supplant human review, but should be used as a culling mechanism – similar to, but much more effective than, keyword search:
“It is important to note that… TAR [Technology Assisted Review] is being used to cull documents prior to human review; the same way keyword search has been used in the past. TAR is not being used as a complete substitute for human review. Every document identified by TAR as potentially responsive is expected to be manually reviewed and then produced if it is found to be responsive and not privileged.”
I frankly share their views. We should be encouraging the adoption of intelligently designed review models to reduce the burden and cost of electronic discovery.
But we should go further than that, should we not? Let’s start with an affirmation: we accept the premise that AR saves time and money, and is more effective than keyword searches alone. Let’s also, at the same time, affirm that when we talk about AR, we talk about its application during the Review phase of the EDRM. There is, I would argue, a benign explanation for this: eDiscovery practitioners, whether technologists or attorneys, tend to cluster in law firms. No question there are thought leaders in the AR space who don’t reside in law firms, but rather at corporations and service bureaus, both large and small. And of course, we can’t forget the judicial advocates of AR. But most practitioners reside in the law firm space, or primarily service law firms, or interact with AR through law firms (vendors and judges). And so they frame AR in terms of where they begin interacting with data – in the middle and right side of the EDRM. It’s only natural that they do so.
And certainly, more and more thought leaders have begun thinking of eDiscovery from an enterprise perspective; that is, corporations, both large and small, are beginning to take control over their eDiscovery destinies, rather than rely on outside counsel to do so. This is, in my view, and an extremely positive development, one that I’ve sought to be ahead of in my decade in the eDiscovery space. But the fact remains that most discussions of AR focus on the review of ESI inside a law firm.
But why not move AR leftward – into the realm of Information Governance? Why not use these intelligent classification systems to categorize and cull unstructured data at the enterprise level, before litigation or the threat of it, arises? In other words, let’s develop a Technology Assisted Governance (TAG) protocol.
Corporations could deploy an intelligent TAG program to re-orient the efficiencies of AR so that they take place well before the review of ESI begins in a law firm. In so doing, law firm attorneys can review documents that have already received the AR treatment, before they’re subject to litigation – and then perhaps can be subject to the process again, once the details of a particular matter or investigation are known. The numerous applications of TAG would occur, in a best-case scenario, before the data was collected and distributed to outside counsel for review.
Now, obviously this brings certain challenges. The AR methodology employed by the corporation will obviously have to be designed with GRC (Governance, Risk, and Compliance) issues in mind, and will be subject to examination by certain bodies who want to ensure that relevant data isn’t culled or classified for deletion. There are a myriad other challenges that will arise from bringing AR behind the firewall. But they are challenges that smart attorneys and technologists can, in my estimation, address over time.
The fact remains that corporations are best-suited to classify their own data. We should work with them to implement a model that will empower them to do just that in a defensible and repeatable way.
Technology Assisted Governance is the right solution.
The author is Vice President of eDiscovery Services for TERIS, and has spent nearly a decade consulting law firms and corporations on eDiscovery and Information Governance strategy.