Maura Grossman and Gordon Cormack just released another blockbuster article, “Comments on ‘The Implications of Rule 26(g) on the Use of Technology-Assisted Review,’” 7 Federal Courts Law Review 286 (2014). The article was in part a response to an earlier article in the same journal by Karl Schieneman and Thomas Gricks, in which they asserted that Rule 26(g) imposes “unique obligations” on parties using TAR for document productions and suggested using techniques we associate with TAR 1.0 including: Continue reading
Two years ago, it was big news in the world of e-discovery when U.S. Magistrate Judge Andrew J. Peck issued the first judicial opinion expressly approving the use of predictive coding. As other judges followed suit, issuing their own opinions endorsing or approving predictive coding, the trend led law firm Gibson Dunn, in its annual e-discovery update, to declare 2012 “the year of predictive coding.”
The trend towards judicial acceptance of predictive coding and other forms of technology assisted review (TAR) has continued, to the point where it is now newsworthy when a judge declines to order TAR. Continue reading
This past weekend I received an advance copy of a new research paper prepared by Gordon Cormack and Maura Grossman, “Evaluation of Machine-Learning Protocols for Technology-Assisted Review in Electronic Discovery.” They have posted an author’s copy here.
The study attempted to answer one of the more important questions surrounding TAR methodology: Continue reading
The purpose of the article was to report on several successful uses of technology-assisted review. While that was interesting, my attention was drawn to another aspect of the report. Three of the case studies provided data shedding further light on that persistent e-discovery mystery: “How many documents in a gigabyte?” Continue reading
[This article originally appeared in Legal IT Insider.]
Asian countries are just starting to come of age in e-discovery. While e-discovery is becoming better understood, more broadly accepted and more thoroughly localized worldwide, the industry is still in its infancy in the APAC region. Because Japan and South Korea are home to some of the largest corporations doing business in the U.S., I’ve focused this article on those two countries.
In Japan, there are no laws governing e-discovery for domestic litigation. Yet an expectation of data production exists for government investigations and international litigation matters. Consequently, U.S. law firms and vendors currently drive e-discovery in Japan. Continue reading
Did you know that Catalyst Insight includes a variety of “hotkey” shortcuts that can help save costly reviewer time? Would you know how to conduct a search for initials in Insight without also bringing up every word in which those letters appear together?
You can learn tips and tricks such as these by following the newly launched training blog from Catalyst’s training department. The blog is intended to help users get the most out of Catalyst’s products such as Insight and Insight Predict. The blog will also provide announcements of new and updated training materials and of updates to products and features. Continue reading
[This article originally appeared in the Winter 2014 issue of EDDE Journal, a publication of the E-Discovery and Digital Evidence Committee of the ABA Section of Science and Technology Law.]
Although still relatively new, technology-assisted review (TAR) has become a game changer for electronic discovery. This is no surprise. With digital content exploding at unimagined rates, the cost of review has skyrocketed, now accounting for over 70% of discovery costs. In this environment, a process that promises to cut review costs is sure to draw interest, as TAR, indeed, has.
Called by various names—including predictive coding, predictive ranking, and computer-assisted review—TAR has become a central consideration for clients facing large-scale document review. It originally gained favor for use in pre-production reviews, providing a statistical basis to cut review time by half or more. It gained further momentum in 2012, when federal and state courts first recognized the legal validity of the process. Continue reading
The head of Catalyst’s South Korea office, Youngsoo Park, is the coauthor with Jeongho Yoo of a just-published Korean-language book about e-discovery for business leaders. The book, What Every Business Person Should Know about eDiscovery, provides a comprehensive overview of all aspects of e-discovery.
The book is only the second ever about e-discovery published in Korea and the first in which hands-on professionals explore the topic in depth. The book covers the history and basics of e-discovery and then examines key topics and legal issues in e-discovery practice, both in the United States and Korea. It also explains several of the leading technology platforms for e-discovery, including Catalyst Insight. The book was published earlier this month in Seoul by InfoTheBooks.com.
Park, who is considered one of the leading e-discovery experts in Korea, joined Catalyst in 2013, when the company opened its first office in Seoul. He oversees the office and the expansion of Catalyst’s Asia-Pacific operations into South Korea. Continue reading
Predictive Ranking, aka predictive coding or technology-assisted review, has revolutionized electronic discovery–at least in mindshare if not actual use. It now dominates the dais for discovery programs, and has since 2012 when the first judicial decisions approving the process came out. Its promise of dramatically reduced review costs is top of mind today for general counsel. For review companies, the worry is about declining business once these concepts really take hold.
While there are several “Predictive Coding for Dummies” books on the market, I still see a lot of confusion among my colleagues about how this process works. To be sure, the mathematics are complicated, but the techniques and workflow are not that difficult to understand. I write this article with the hope of clarifying some of the more basic questions about TAR methodologies. Continue reading
On Jan. 24, Law Technology News published John’s article, “Five Myths about Technology Assisted Review.” The article challenged several conventional assumptions about the predictive coding process and generated a lot of interest and a bit of dyspepsia too. At the least, it got some good discussions going and perhaps nudged the status quo a bit in the balance.
One writer, Roe Frazer, took issue with our views in a blog post he wrote. Apparently, he tried to post his comments with Law Technology News but was unsuccessful. Instead, he posted his reaction on the blog of his company, Cicayda. We would have responded there but we don’t see a spot for replies on that blog either. Continue reading