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2012 has been called by some “The Year of Technology Assisted Review.” What does that mean, and why is that? In 2011, the amount of information created and replicated surpassed 1.8 zettabytes (1.8 trillion gigabytes) – and is likely to continue doubling every two years. Unfortunately, the old tools – the old methods – aren’t enough to keep up with the increasing volumes. Computer-assisted review enables human reviewers to train their computers to identify documents that are responsive or not responsive to the topics.

Although there are only a few decisions about the use of these types of technology, judicial commentary does support the use of computer-assisted review. It’s worth repeating Judge Andrew Peck, “This judicial opinion now recognizes that computer-assisted review is an acceptable way to search for relevant ESI in appropriate cases.”

Why? How many attorneys does it take to review 25 million documents? How long will it take and how much will it cost? Consider the initial merger effort of SBC and AT&T and the ensuing Second Request. Using traditional linear methods, this type of review would take 700 attorneys almost 400,000 hours to complete. And even with lower cost contract attorneys, the cost is more than $29 million dollars. This might be a good investment or even necessary for a $16.9 billion dollar deal, but not realistic in most review situations.

Computer technology played a role in the creation and storage of all these potentially relevant documents (including lots of duplicates and near duplicates). It makes sense to leverage advances in computer technology and processing power to tackle some of the large volumes of documents these same advances make possible.

Basic keyword searching (or expanded Boolean) is an established and effective way to reduce volume and attain precision. However, recent studies show that using keyword searching to cull data leaves many relevant documents behind. If we search for banana, we will find banana. But we won’t find “long yellow fruit that grows on trees in tropical climates” … we need more help.

Arguably, the cost associated with reviewing large volumes of documents is enough to motivate us to use any help we can get to reduce these costs. But the quality of these reviews and, ultimately, the quality of produced documents can’t be overlooked. Judge Paul Grimm has often been quoted, “Although basic keyword searching techniques have been widely accepted … as sufficient to define the scope of their obligation to perform a search for responsive documents … simple keyword searching alone is inadequate in at least some discovery contexts. This is because simple keyword searches end up being both over- and under-inclusive in light of the inherent malleability and ambiguity of spoken and written English.” Even before this enlightenment – Judge John Facciola was recorded as saying, “I bring to the parties’ attention recent scholarship that argues that concept searching, as opposed to keyword searching, is more efficient and more likely to produce the most comprehensive results.”

Large scale review doesn’t play to the strengths of human reviewers. Factors such as low motivation, the review being a tedious task, fatigue or teams mixed with varying degrees of knowledge can result in productions with very low recall rates.  Several new tools are available to increase the number of documents a reviewer can review per hour. These tools include clustering, email thread analysis, near-duplicate identification, conceptual searching, metadata analysis, and domain filtering.

Technology-assisted review, also known as predictive coding, is another new tool. When talking about computer-assisted review, it’s important to understand precision and recall, two terms from information retrieval science. Precision is the percentage of documents returned by a search that are relevant, and Recall  is the percentage of all relevant documents returned by a search. Our goal is to maximize Recall while achieving acceptable Precision.

There are many tools and applications to choose from when committing to this type of review technology. Iteration is a consistent factor in the different technologies. Successful adoption relies on a combination of sound technology, expert reviewer, and defensible process. Place emphasis on the review workflow. There are easy to understand processes that can be followed.

Subject matter experts review a small subset of the document population. These documents are ranked, results are measured, repeat. These batches go through quality control and overturn cleanup. Different technologies use different ranking systems, but, ultimately, once the human has adequately trained the system, it can rank the entire population of documents. Now we have rankings of relevancy or discrete buckets of relevant and non-relevant data (a small amount of uncategorized is to be expected as well).

It’s important to note that the documents considered by the system to be most likely relevant are typically reviewed to improve precision and identify any privileged or confidential documents. This assisted workflow reduces the amount of time in which humans are provided with a rich set of potentially relevant documents to review. The non-relevant data should have sufficient levels of quality control. The potentially relevant data is now ready for the earlier technologies discussed. Simple linear review could be used, or advance organizational structure or concept searching will continue to assist in the productivity and quality of the review. The continued use of computer-assisted technology in the review workflow will help identify potentially privileged documents as well as identify documents related to issues.

To cope with 2012 levels of electronically stored information, eDiscovery teams need to adopt 2012 methods and tools. Bring tools and techniques in house or work with service organizations that have specialist teams and established tools and processes. As technology advances have enabled people to generate these large volumes of documents, we can leverage technology advances to keep eDiscovery effective and reasonable.

Adam Bowen

Adam Bowen is a Solutions Architect at DTI. He is responsible for engaging in the development and implementation of client-specific electronic discovery solutions, including forensics and data collection, processing work flow, hosting services and document review services. Adam has been in the litigation support space for over 17 years, working with both in-house legal counsels and Law Firms across the United States.

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Filed Under: Featured StoriesTechnology

About the Author: Adam Bowen is a Solutions Architect at DTI. He is responsible for engaging in the development and implementation of client-specific electronic discovery solutions, including forensics and data collection, processing work flow, hosting services and document review services. Adam has been in the litigation support space for over 17 years, working with both in-house legal counsels and Law Firms across the United States.

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