Even with a large pool of participants, ample time, and the ability to hone search queries based on instant feedback, nobody was able to generate a better production than Technology-Assisted Review (TAR) when the same amount of review effort was expended. It seems fair to say that keyword search often requires twice as much document review to achieve a production that is as good as what you would get TAR.
The Predictive Coding Technologies and Protocols Survey is a non-scientific survey designed to help provide a general understanding of the use of predictive coding technologies, protocols, and workflows by data discovery and legal discovery professionals within the eDiscovery ecosystem.
Technology Assisted Review (TAR) is useful for many tasks within the Electronic Discovery Reference Model (EDRM), with one of its central applications being its use in determining the relevancy of documents in the review stage of eDiscovery in support of document production obligations. To engage in the management of this important workflow, the producing party needs access to TAR software and the decision on what software to use goes hand-in-hand with the service provider selection.
EDRM has released a comprehensive set of guidelines that aim to objectively define and explain technology-assisted review for members of the judiciary and the legal profession. The TAR Guidelines represent the first step in a multifaceted effort to develop a broad understanding of TAR and to encourage its adoption. Under the auspices of the Bolch Judicial Institute and EDRM, a second document, a protocol for when and under what circumstances TAR should be used, is currently being developed by a drafting team of 40 judges, lawyers, and e-discovery experts who attended a 2017 conference focused on TAR best practices, hosted by Duke and EDRM.
eDiscovery expert Dr. Bill Dimm explains why some performance metrics don’t give an accurate view of performance for eDiscovery purposes, and why that makes a lot of research utilizing such metrics irrelevant for eDiscovery.
In this fifth round of Bill Dimm’s TAR vs. Keyword Search Challenge, TAR beat the keyword searches by a huge margin.
Even the best queries had lower recall with review of 6,000 documents than TAR 3.0 CAL achieved with review of only 3,000 documents, but a few of the queries did achieve higher recall than TAR 3.0 SAL when twice as much document review was performed with the search query compared to TAR 3.0 SAL.
If there is any shortcoming of TAR technologies, the blame may fairly be placed at the feet (and in the minds) of humans.
The Predictive Coding Technologies and Protocols Survey is a non-scientific survey designed to help provide a general understanding of the use of predictive coding technologies and protocols from data discovery and legal discovery professionals within the eDiscovery ecosystem.
Technology-Assisted Review is being used increasingly and, combined with recently-proposed changes to the English disclosure regime, could result in more legal cases becoming economically viable to fight and lead to greater recoveries for creditors.