Source: https://blog.x1discovery.com/tag/litigation/
Timestamp: 2019-04-25 06:07:32+00:00

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Predictive Coding, when correctly employed, can significantly reduce legal review costs with generally more accurate results than other traditional legal review processes. However, the benefits associated with predictive coding are often undercut by the over-collection and over-inclusion of Electronically Stored Information (ESI) into the predictive coding process. This is problematic for two reasons.
The first reason is obvious, the more data introduced into the process, the higher the cost and burden. Some practitioners believe it is necessary to over-collect and subsequently over-include ESI to allow the predictive coding process to sort everything out. Many service providers charge by volume, so there can be economic incentives that conflict with what is best for the end-client. In some cases, the significant cost savings realized through predictive coding are erased by eDiscovery costs associated with overly aggressive ESI inclusion on the front end.
The second reason why ESI over-inclusion is detrimental is less obvious, and in fact counter intuitive to many. Some discovery practitioners believe as much data as possible needs to be put through the predictive coding process in order to “better train” the machine learning algorithms. However this is contrary to what is actually true. The predictive coding process is much more effective when the initial set of data has a higher richness (also referred to as “prevalence”) ratio. In other words, the higher the rate of responsive data in the initial data set, the better. It has always been understood that document culling is very important to successful, economical document review, and that includes predictive coding.
Robert Keeling, a senior partner at Sidley Austin and the co-chair of the firm’s eDiscovery Task Force, is a widely recognized legal expert in the areas of predictive coding and technology assisted review. At Legal Tech New York earlier this year, he presented at an Emerging Technology Session: “Predictive Coding: Deconstructing the Secret Sauce,” where he and his colleagues reported on a comprehensive study of various technical parameters that affect the outcome of a predictive coding effort. According to Robert, the study revealed many important findings, one of them being that a data set with a relatively high richness ratio prior to being ingested into the predictive coding process was an important success factor.
To be sure, the volume of ESI is growing exponentially and will only continue to do so. The costs associated with collecting, processing, reviewing, and producing documents in litigation are the source of considerable pain for litigants. The only way to reduce that pain to its minimum is to use all tools available in all appropriate circumstances within the bounds of reasonableness and proportionality to control the volumes of data that enter the discovery pipeline, including predictive coding.
Ideally, an effective early case assessment (ECA) capability can enable counsel to set reasonable discovery limits and ultimately process, host, review and produce less ESI. Counsel can further use ECA to gather key information, develop a litigation budget, and better manage litigation deadlines. ECA also can foster cooperation and proportionality in discovery by informing the parties early in the process about where relevant ESI is located and what ESI is significant to the case. And with such benefits also comes a much more improved predictive coding process.
X1 Distributed Discovery (X1DD) uniquely fulfills this requirement with its ability to perform pre-collection early case assessment, instead of ECA after the costly, time consuming and disruptive collection phase, thereby providing a game-changing new approach to the traditional eDiscovery model. X1DD enables enterprises to quickly and easily search across thousands of distributed endpoints from a central location. This allows organizations to easily perform unified complex searches across content, metadata, or both and obtain full results in minutes, enabling true pre-collection ECA with live keyword analysis and distributed processing and collection in parallel at the custodian level. To be sure, this dramatically shortens the identification/collection process by weeks if not months, curtails processing and review costs from not over-collecting data, and provides confidence to the legal team with a highly transparent, consistent and systemized process. And now we know of another key benefit of an effective ECA process: much more accurate predictive coding.
The eDiscovery update addresses key themes and several cases involving key legal issues related to social media evidence, which were previously addressed on this blog. Two key highlights cite cases affirming that mere screenshot printouts of social media evidence are not defensible and clarify overall authentication requirements in order to admit social media evidence in court.
As noted by the report “in the first half of 2015, courts continued to find that the testimony of the individual who printed a copy of a social media webpage, or prepared a memorandum summarizing information obtained from the social media account, is insufficient to authenticate social media evidence.” The report cites Linscheid v. Natus Medical Inc., 2015 WL 1470122, at *5-6 (N.D. Ga. Mar. 30, 2015) (finding LinkedIn profile page not authenticated by declaration from individual who printed the page from the Internet); Monet v. Bank of America, N.A., 2015 WL 1775219, at *8 (Cal Ct. App. Apr. 16, 2015) (finding that a “memorandum by an unnamed person about representations others made on Facebook is at least double hearsay” and not authenticated).
The Report also cited “a major shift” in case law concerning the authentication of social media evidence. The Court of Appeals of Maryland determined that “in order to authenticate evidence derived from a social networking website, the trial judge must determine that there is proof from which a reasonable juror could find that the evidence is what the proponent claims it to be.” Sublet v. State, 113 A.3d 695, 698, 718, 722 (Md. 2015) (citing U.S. v. Vayner, 769 F.3d 125 (2d Cir. 2014)). Previously in Maryland, social media evidence was admissible only if the judge was “convince[d] . . . that the social media post was not falsified or created by another user.” Griffin v. State, 19 A.3d 415 (Md. 2011).
These cases cited by Gibson Dunn illustrate why best practices software is needed to properly collect and preserve social media evidence. Ideally, a proponent of the evidence can rely on uncontroverted direct testimony from the creator of the web page in question. In many cases, such as in the Vayner case where incriminating social media evidence is at issue, that option is not available. In such situations, the testimony of the examiner who preserved the social media or other Internet evidence “in combination with circumstantial indicia of authenticity (such as the dates and web addresses), would support a finding” that the website documents are what the proponent asserts. Perfect 10, Inc. v. Cybernet Ventures, Inc. (C.D.Cal.2002) 213 F.Supp.2d 1146, 1154. (emphasis added) (See also, Lorraine v. Markel American Insurance Company, 241 F.R.D. 534, 546 (D.Md. May 4, 2007) (citing Perfect 10, and referencing MD5 hash values as an additional element of potential “circumstantial indicia” for authentication of electronic evidence).
One of the many benefits of X1 Social Discovery is its ability to preserve and display all the available “circumstantial indicia” or “additional confirming circumstances,” in order to present the best case possible for the authenticity of social media evidence collected with the software. This includes collecting all available metadata and generating a MD5 checksum or “hash value” of the preserved data for verification of the integrity of the evidence. It is important to collect and preserve social media posts and general web pages in a thorough manner with best-practices technology specifically designed for litigation purposes. For instance, there are over twenty unique metadata fields associated with individual Facebook posts and messages. Any one of those entries, or a combination of them contrasted with other entries, can provide unique circumstantial evidence that can establish foundational proof of authorship.
In recent months, courts in several reported decisions have excluded evidence in the form of screen captures of social media. These court decisions greatly impacted the overall matter, including directly resulting in the overturning of a criminal conviction. This is a very important trend as many criminal investigators and litigation support practitioners continue to rely on print screen without realizing the now torrent level of case law disallowing such evidence.
In the most recent example, in Moroccanoil vs. Marc Anthony Cosmetics, — F.Supp.3d —- (2014) a federal district court explicitly ruled that Facebook screenshots were inadmissible as the defendant in a trademark infringement action merely offered the screenshots without supporting circumstantial information, which is difficult to obtain when mere screenshots are relied upon. The Moroccanoil court cited Internet Specialties W., Inc. v. ISPWest, 2006 WL 4568796 which in that case ruled: “Defendant’s argument, that [web pages] could be ‘authenticated’ by the person who went to the website and printed out the home page, is unavailing.” The Moroccanoil court applied the same rule to Facebook screenshots.
In the criminal context, in United States vs. Vayner, 2014 WL 4942227 (C.A. 2 (N.Y.)), A US Federal Appellate Court, Second Circuit, recently overturned a criminal conviction upon finding that the lower court erroneously admitted a screenshot of the defendant’s alleged social media profile due to improper authentication. Earlier this year, in Commonwealth v. Banas, 2014 WL 1096140 a Massachusetts Appellate Court also ruled that a screen print of Facebook post submitted by the prosecution in a criminal case to be inadmissible on authentication grounds.
The courts that produced these decisions are very influential and these decisions will impact standards for, and the scrutiny of, all social media evidence collection in criminal and civil matters nationwide.
The cases cited above and many others like them illustrate that social media provides torrential amounts of evidence potentially relevant to litigation matters, with courts routinely facing proffers of data preserved from various social media websites. One of the many benefits of X1 Social Discovery is its ability to preserve and display all the available circumstantial evidence in order to present the best case possible for the authenticity of social media evidence collected with the software. This includes collecting all available metadata and generating a MD5 checksum or “hash value” of the preserved data for verification of the integrity of the evidence. It is important to collect and preserve social media posts and general web pages in a thorough manner with best-practices technology specifically designed for litigation purposes. For instance, there are over twenty unique metadata fields associated with individual Facebook posts and messages. Any one of those entries, or a combination of them contrasted with other entries, can provide unique circumstantial evidence that can establish foundational proof of authorship. (We identify the nearly two dozen fields of unique Twitter metadata in our white paper available here).
So in sum, you can either have your cake and eat it too with X1, or incur much higher costs, overlook mountains of potentially case-winning evidence, arguably violate your ethical duty of competence, and face evidentiary challenges in court with print screen. Seems like an easy decision.

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