While the Electronic Discovery Reference Model from EDRM has become the standard model for the workflow of the process for handling electronically stored information (ESI) in discovery, it might be helpful to think about the EDRM model backwards, whether you’re the producing party or the receiving party.
Among the many definitions of the word “zen”, the Urban Dictionary provides perhaps the most appropriate (non-religious) definition of the word, as follows: a total state of focus that incorporates a total togetherness of body and mind. However, when it comes to document review, a new web site by eDiscovery thought leader Ralph Losey may change your way of thinking about the word “ZEN”.
Yesterday, we discussed how corporate logo graphic files in email signatures can add complexity when managing those emails in eDiscovery, as these logos, repeated over and over again, can add up to a significant percentage of your collection on a file count basis. Today, we are going to discuss a couple of ways that I have worked with clients to manage those files during the review process.
A couple of weeks ago, a $384 million class action was filed in Canada against professional services firm Deloitte LLP on behalf of hundreds of lawyers working at a document-review company it acquired last year. Even in Canadian dollars, that’s a lot.
In Rio Tinto Plc v. Vale S.A., New York Magistrate Judge Andrew J. Peck approved the proposed protocol for technology assisted review (TAR) presented by the parties, but made it clear to note that “the Court's approval ‘does not mean. . . that the exact ESI protocol approved here will be appropriate in all [or any] future cases that utilize [TAR].’”
Today’s thought leader is Brad Jenkins of CloudNine™. Brad has over 20 years of experience as an entrepreneur, as well as 15 years leading customer focused companies in the litigation support arena. Brad has authored several articles on document management and litigation support issues, and has appeared as a speaker before national audiences on document management practices and solutions. He’s also my boss!
It’s not Desi Arnaz who wants it, but the Discovery of Electronically Stored Information (DESI) VI workshop, which is being held at the University of San Diego on June 8 as part of the 15th International Conference on Artificial Intelligence & Law (ICAIL 2015).
They say that a joke is only old if you haven’t heard it before. In that vein, an article about eDiscovery is only old if you haven’t read it before. Craig Ball is currently revisiting some topics that he covered ten years ago with an updated look, making them appropriate for 1) people who weren’t working in eDiscovery ten years ago (which is probably a lot of you), 2) people who haven’t read the articles previously and 3) people who have read the articles previously, but haven’t seen his updated takes. In other words, everybody.
As we noted yesterday and the day before, eDiscoveryDaily published 93 posts related to eDiscovery case decisions and activities over the past year, covering 68 unique cases! Yesterday, we looked back at cases related to eDiscovery cost sharing and reimbursement, fee disputes and production format disputes. Today, let’s take a look back at cases related to privilege and inadvertent disclosures, requests for social media, cases involving technology assisted review and the case of the year – the ubiquitous Apple v. Samsung dispute.
In Good v. American Water Works, West Virginia District Judge John T. Copenhaver, Jr. granted the defendants' motion for a Rule 502(d) order that merely encouraged the incorporation and employment of time-saving computer-assisted privilege review over the plaintiffs’ proposal disallowing linear privilege review altogether.
A couple of months ago, we had a laugh at Ralph Losey’s post that took a humorous look at the scenario where it’s Friday at 5 and you need data processed to be reviewed over the weekend. It was a funny take on a real problem that most of us have experienced from time to time. But, there may be a solution to this problem that’s automated, easy and inexpensive.
Today is Halloween. Every year at this time, because (after all) we’re an eDiscovery blog, we try to “scare” you with tales of eDiscovery horrors. This is our fifth year of doing so, let’s see how we do this year. Be afraid, be very afraid!
In Price Waicukauski & Riley v. Murray, Indiana District Judge William T. Lawrence granted the plaintiff’s request for summary judgment for failure to pay attorney’s fees of over $125,000, and refused to issue summary judgment for either party related to a legal malpractice claim for the plaintiff’s admitted failure to review documents produced in the defendants’ case against another party because of a factual dispute regarding the plaintiff’s knowledge of the documents produced.
A new self-assessment resource from EDRM helps you answer that question. A few days ago, EDRM announced the release of the EDRM eDiscovery Maturity Self-Assessment Test (eMSAT-1), the “first self-assessment resource to help organizations measure their eDiscovery maturity”. Find out more about it here.
In Dynamo Holdings v. Commissioner of Internal Revenue, Texas Tax Court Judge Ronald Buch ruled that the petitioners “may use predictive coding in responding to respondent's discovery request” and if “after reviewing the results, respondent believes that the response to the discovery request is incomplete, he may file a motion to compel at that time”.
As we discussed Wednesday, working with electronic files in a review tool is NOT just simply a matter of loading the files and getting started. Electronic files are diverse and can represent a whole collection of issues to address in order to process them for loading. To address those issues effectively, processing requires a sound process.
Since hard copy discovery became electronic discovery, I’ve worked with a number of clients who expect that working with electronic files in a review tool is simply a matter of loading the files and getting started. Unfortunately, it’s not that simple!
I frequently get asked how big does an ESI collection need to be to benefit from eDiscovery technology. In a recent case with one of my clients, the client had a fairly small collection – only about 4 GB. But, when a judge ruled that they had to start conducting depositions in a week, they needed to review that data in a weekend. But, if you’re not facing a tight deadline, how large does your collection need to be for the use of eDiscovery technology to provide benefits?
A lot of people consider Technology Assisted Review (TAR) and Predictive Coding (PC) to be new technology. We attempted to debunk that as myth last year after our third annual thought leader interview series by summarizing comments from some of the thought leaders that noted that TAR and PC really just apply artificial intelligence to the review process. But, the foundation for TAR may go way farther back than you might think.
In Bridgestone Americas Inc. v. Int'l Bus. Mach. Corp., Tennessee Magistrate Judge Joe B. Brown, acknowledging that he was “allowing Plaintiff to switch horses in midstream”, nonetheless ruled that that the plaintiff could use predictive coding to search documents for discovery, even though keyword search had already been performed.
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