Source: https://www.xactdatadiscovery.com/topic/predictive-coding/
Timestamp: 2019-04-21 15:07:13+00:00

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Just as a search or a TAR tool is making a series of binary classification decisions, so too are your human reviewers, and the quality of those reviewers’ decisions can be assessed in a similar manner to how you assessed the quality of a search classifier. Depending on the scale of your review project, employing these assessment methods can be more efficient and informative.
Sampling can be used to test your search classifiers – whether keyword searches, TAR software, or other tools – by calculating their recall (efficacy) and precision (efficiency). Doing so requires a previously-reviewed control set, contingency tables, and some simple math.
Beyond estimating prevalence, there are other opportunities to replace informal sampling of unknown reliability with formal sampling of precise reliability. Imagine iteratively refining searches for your own use, or negotiating with another party about which searches should be used, armed with precise, reliable information about their relative efficacy. Using sampling to test classifiers can facilitate this.
Over the course of this survey, we have taken an in-depth look at a dozen cases and touched briefly on eleven others. Together, these twenty-three cases have provided us with an effective overview of the technology-assisted review case law landscape, including what’s been settled and what remains unresolved. We conclude our survey with a discussion of the five key takeaways we can derive from our review of these cases.
Before we conclude our survey of technology-assisted review cases, there are a handful of additional cases worth noting that did not warrant full posts of their own. Specifically, there are three more early cases, three more recent cases, and five international cases worth noting.
The next prominent technology-assisted review case requiring our attention is Winfield v. City of New York (S.D.N.Y. Nov. 27, 2017). The case wound up before the Magistrate Judge for the resolution of a variety of discovery disputes, including the Plaintiffs’ challenges to the City’s TAR process and their attempts to compel additional transparency regarding that process.
The next major TAR case for us to review is the third and final prominent case on the topic from Magistrate Judge Peck. In Hyles v. New York City (S.D.N.Y. Aug. 1, 2016), a series of discovery delays and conflicts led to the referral of the case to Magistrate Judge Peck, who resolved a number of discovery questions for the parties, including the question of whether a requesting party can compel a producing party to use TAR.
The next prominent TAR case was Rio Tinto PLC v. Vale, S.A., et al. (S.D.N.Y. Mar. 2, 2015), which was another decision from Magistrate Judge Peck. This is another case in which the parties reached an agreement about the use of TAR, but the Magistrate Judge’s order accepting their agreement still provides an excellent summary of the state of TAR acceptance as of spring 2015, after the first three years of cases.
The next TAR case to make headlines was Dynamo Holdings Limited Partnership, et al., v. Commissioner of Internal Revenue (USTC Sep. 17, 2014), which was a U.S. Tax Court case. The case was the first in which the U.S. Tax Court approved the use of technology-assisted review, and it addressed the question of whether prior approval for TAR use should be sought.
The next prominent TAR case was In Re: Biomet M2a Magnum Hip Implant Products Liability Litigation (N.D. Ind. Aug.21, 2013), which was consolidated multidistrict product liability litigation. The litigation was eventually settled, but not before substantial discovery work was done and two orders concerning the use of TAR were issued.
The next significant TAR case was In Re: Actos (Pioglitazone) Products Liability Litigation (W.D. La. Jul. 27, 2012), which provided the first on-the-record example of a TAR protocol successfully and cooperatively negotiated by the parties. It provided for testing of suitability before the full effort, plans for transparency and cooperation throughout the effort, and validation steps to measure the success of the effort.
The next major TAR case after da Silva Moore was Kleen Products LLC, et al., v. Packaging Corporation of America, et al. (N.D. Ill. Aug. 21, 2012), which was significant for its analysis of the method selection question and for its very educational hearing transcripts, which include extensive discussion of Boolean searching, technology-assisted review, and validation methodologies.
The year after technology-assisted review first rose to prominence in eDiscovery, Monique da Silva Moore, et al., v. Publicis Groupe SA & MSL Group (S.D.N.Y. Feb. 24, 2012) became the first case in which the use of TAR was judicially approved, and Magistrate Judge Peck’s order approving its use in that case included topical education and legal analysis that was very impactful during TAR’s rise.
Technology-assisted review (“TAR”) first rose to prominence in the legal industry around 2011 under the name predictive coding. Although growth has remained slower than expected, signs of TAR’s continued growth and importance abound, and case law continues to accumulate. From 2012’s da Silva Moore, to 2017’s Winfield and beyond, this series will survey the case law in this area to provide you with the available guidance from the courts.
Relativity 9.1 includes some key new features. This blog post from Carl Chivers shares what you need to know!
With e-discovery tools becoming increasingly affordable, smaller firms have access to the same technologies employed by large law firms ‒ or sometimes even better ones. Small and midsize firms are better positioned to compete for large clients than ever before.
Why use Technology Assisted Review (TAR)? Saving review costs is a big reason, but improved resource management is a key benefit.
It is commonplace today to have documents within eDiscovery collections that contain foreign languages, but this no longer need to be an obstacle for English-speaking legal teams. Handling documents in foreign languages has become much simpler and more cost-effective than in years past, and legal teams should understand their options.
XDD’s Chris Chapman recaps a recent CLE event featuring an in-depth discussion from a panel of Federal Judges, offering a unique judicial perspective on the use of technology-assisted review.
Know the factors that help determine when computer-assisted review is the right tool for the job, so you’ll be well-prepared to present your proportionality argument and get your CAR discovery plan approved by the court.
In this era of Big Data, companies can take steps to reduce the costs of defending themselves in litigation.

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