How to Streamline Disclosure Process with Technology Assisted Review (TAR)?

Technology is taking over the front seat in every sphere of life and the legal profession is no exception. One of the areas that are being encouraged by courts and tribunals around the world is the introduction of technology assisted review (TAR) in the disclosure process. It is particularly helpful when large volumes of documents in complex cases have to be analyzed.

However, it has to be kept in mind that TAR is not an automated process of document review. It requires vigilance and expertise on the part of lawyers monitoring the process to optimize the effectiveness of TAR and ensure that no slip-ups occur at any stage.

What is TAR?

TAR is a broad term that denotes any tool or approach to document review. Any technology that facilitates the legal document and management review process and makes it more efficient and reliable than the traditional manual procedures is said to be covered under TAR. It eases the process and is suitable for cases where voluminous amounts of documents have to be reviewed and analyzed. Even in small cases, TAR may be used to serialize or cluster documents so that they may be presented to human reviewers in an orderly fashion.

The gains from TAR are usually more conspicuous in instances where the number of documents under review is typically greater than a hundred thousand. The potential efficiencies that can be had from this process have to be matched against costs incurred on document review services. This is not standardized and differs from case to case and the amounts under litigation.

The process of TAR includes the following concepts and activities:

• Predictive coding–
  Statistical models based on definite algorithms are used to recall documents similar to a sample set. This sample set is referred to as a “seed set”. A reviewer then verifies whether the documents recalled are consistent with the seed set. Once checked, the documents are again fed back into the algorithm thereby increasing the size of the “seed set”. This form of predictive coding cannot be used as a substitute for subjective document review as the latter has to be gone through to ensure consistency and integrity of results.

• Concept Cluttering–

  This term is used to denote document sets or search results that are in an interactive and graphical format. TAR ensures that documents with similar content are clustered together even though the display configurations may vary between legal back office service providers.

• Email threading–

  This is the process where statistical methods are used to link up emails that are similar in nature but cannot be considered identical to each other. Examples are email chains which branch off in content from a main email thread or emails that are forwarded to different recipients.

• Identification of near-duplicates–

  Like email threading, it is used to identify and club together documents that are not considered identical but have similar concepts. For this TAR uses “fuzzy” searching, synonyms and custom dictionaries to arrive at a common plank in sorting documents.

How to optimize the use of TAR?

While the expertise of document review services is never in question, optimization in using TAR to its fullest potential depends on following a set of guidelines. Here are a few of them:

• Constant monitoring and vigilance–

  TAR is not an automated process and constant monitoring is necessary to get precise results. Legal back office team has to decide critically which documents have to be pulled out of the pool for subjective review and which can be excluded. Documents recalled by the technology have to be manually reviewed on a sample basis to ensure that the system is working as it should. Once if any corrections are made the algorithm will also be re-tuned based on these modifications.

• Reduce the number of reviewing lawyers–

  Unlike conventional document review where teams of lawyers are engaged, TAR achieves greater efficiencies as only one or two experts review a small sample set to check the accuracy. Once done, the algorithm will do the main work of identifying related documents which can then be checked by a relatively junior team. It is important that the initial work of checking the smaller training set of documents be entrusted to a senior and experienced lawyer only. On an average, a sample set of as few as 3,000 random documents may be verified for one million documents. That is the power of TAR if used judiciously.

• Run multiple TAR processes for disputed issues–

  TAR processes do not work optimally if there are a number of issues or lots of categories for discovery. In such cases, separate TAR procedures have to be performed in each case with lawyers who are experts in different aspects supervising them. There is a downside to running multiple TAR processes because it is difficult to avoid “double-handling” where the same documents will be reviewed more than once for different purposes.

• Create “example documents”–

  The legal team may create “example documents” and then let the algorithm find similar documents. This is usually done to test whether the system is working as required. These documents should be so created that they are used as a testing tool for email threading and other cluster tools. The dummy document should be quarantined after the testing is over and left out of any disclosure processes.

• TAR is not infallible and should be treated as such–

  While TAR has great benefits, it is not infallible. It identifies documents by the content in them only and not what is excluded. But that too can be used to advantage. A fraud if concealed in a daily report intentionally over time will also be pulled up in TAR. The fact that it is not there in all documents will establish the matter of intentional concealment. Similarly, TAR does not work on photographs, drawings, and spreadsheets.

Follow these guidelines to get the best out of TAR to streamline the document review process.

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