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.
The Predictive Coding Technologies and Protocols Survey is a non-scientific semi-annual survey designed to help provide a general understanding of the current application of predictive coding technologies, protocols, workflows, and uses by data discovery and legal discovery professionals.
As your opinion is essential in helping form a complete picture of the interest and impact of predictive coding in eDiscovery, please do take the time to complete this short, anonymized survey, as the results will help legal, business, and technology professionals in the eDiscovery ecosystem better understand the current use of predictive coding.
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.
United gave the passengers more than 3.5 million “core” documents during discovery. But only about 600,000—17 percent— of the documents were responsive to the passengers’ discovery requests.
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.
During this iteration of the TAR vs. Keyword Search Challenge held at the Education Hub at ILTACON 2018, TAR won across the board, as in previous iterations of the challenge.