Analysis

In Brown v BCA Trading, et. al. [2016] EWHC 1464 (Ch), Mr. Registrar Jones ruled that, with “nothing, as yet, to suggest that predictive coding will not be able to identify the documents which would otherwise be identified through, for example, keyword search”, “predictive coding must be the way forward” in this dispute between parties as to whether the Respondents could use predictive coding to respond to eDisclosure requests.

The May 17 order began by noting that “the question whether or not electronic disclosure by the Respondents should be provided, as they ask, using predictive coding or via a more traditional keyword approach instead” was “contested”.  With the “majority of the documents that may be relevant for the purposes of trial…in the hands of the First Respondent”, the order noted that fact is “relevant to take into account when considering the Respondents’ assertion, presented from their own view and on advice received professionally, that they think predictive coding will be the most reasonable and proportionate method of disclosure.”  The cost for predictive coding was estimated “in the region of £132,000” whereas the costs for a key word search approach was estimated to be “at least £250,000” and could “even reach £338,000 on a worst case scenario” (emphasis added).  In the order, it was acknowledged that the cost “is relevant and persuasive only to the extent that predictive coding will be effective and achieve the disclosure required.”

With that in mind, Mr. Registrar Jones stated the following: “I reach the conclusion based on cost that predictive coding must be the way forward. There is nothing, as yet, to suggest that predictive coding will not be able to identify the documents which would otherwise be identified through, for example, keyword search and, more importantly, with the full cost of employees/agents having to carry out extensive investigations as to whether documents should be disclosed or not. It appears from the information received from the Respondents that predictive coding will be considerably cheaper than key word disclosure.”

The order also referenced the ten factors set out by Master Matthews in the Pyrrho Investments case (the first case in England to approve predictive coding) to help determine that predictive coding was appropriate for that case, with essentially all factors applying to this case as well, except for factor 10 (the parties have agreed on the use of the software, and also how to use it).

So, what do you think?  Do you think parties should always have the right to use predictive coding to support their production efforts absence strong evidence that it is not as effective as other means?  Please share any comments you might have or if you’d like to know more about a particular topic.

For more reading about this case, check out Chris Dale’s post here and Adam Kuhn’s post here.

Don’t forget that tomorrow at 1:00pm ET, ACEDS will be conducting a webinar panel discussion, titled How Automation is Revolutionizing eDiscovery, sponsored by CloudNine.  Our panel discussion will provide an overview of the eDiscovery automation technologies and we will really take a hard look at the technology and definition of TAR and the limitations associated with both.  This time, Mary Mack, Executive Director of ACEDS will be moderating and I will be one of the panelists, along with Bill Dimm, CEO of Hot Neuron and Bill Speros, Evidence Consulting Attorney with Speros & Associates, LLC.  Click on the link here to register.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine. eDiscovery Daily is made available by CloudNine solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Daily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

We’re beginning to see more disputes between parties regarding the use of technology assisted review (TAR) in discovery.  Usually in these disputes, one party wants to use TAR and the other party objects.  In this case, the dispute was a bit different…

In Hyles v. New York City, No. 10 Civ. 3119 (AT)(AJP) (S.D.N.Y. Aug. 1, 2016), New York Magistrate Judge Andrew J. Peck, indicating that the key issue before the court in the discovery dispute between parties was whether (at the plaintiff’s request) the defendants can be forced to use technology assisted review, refused to force the defendant to do so, stating “The short answer is a decisive ‘NO.’”

Case Background

In this discrimination case by a former employee of the defendant, after several delays in discovery, the parties had several discovery disputes.  They filed a joint letter with the court, seeking rulings as to the proper scope of ESI discovery (mostly issues as to custodians and date range) and search methodology – whether to use keywords (which the defendants wanted to do) or TAR (which the plaintiff wanted the defendant to do).

With regard to date range, the parties agreed to a start date for discovery of September 1, 2005 but disagreed on the end date.  In the discovery conference held on July 27, 2016, Judge Peck ruled on a date in between what the plaintiff and defendants – April 30, 2010, without prejudice to the plaintiff seeking documents or ESI from a later period, if justified, on a more targeted inquiry basis.  As to custodians, the City agreed to search the files of nine custodians, but not six additional custodians that the plaintiff requested.  The Court ruled that discovery should be staged, by starting with the agreed upon nine custodians. After reviewing the production from the nine custodians, if the plaintiff could demonstrate that other custodians had relevant, unique and proportional ESI, the Court would consider targeted searches from those custodians.

After the parties had initial discussions about the City using keywords, the plaintiff’s counsel consulted an ediscovery vendor and proposed that the defendants should use TAR as a “more cost-effective and efficient method of obtaining ESI from Defendants.”  The defendants declined, both because of cost and concerns that the parties, based on their history of scope negotiations, would not be able to collaborate to develop the seed set for a TAR process.

Judge’s Ruling

Judge Peck noted that “Hyles absolutely is correct that in general, TAR is cheaper, more efficient and superior to keyword searching” and referenced his “seminal” DaSilva Moore decision and also his 2015 Rio Tinto decision where he wrote that “the case law has developed to the point that it is now black letter law that where the producing party wants to utilize TAR for document review, courts will permit it.”  Judge Peck also noted that “Hyles’ counsel is correct that parties should cooperate in discovery”, but stated that “[c]ooperation principles, however, do not give the requesting party, or the Court, the power to force cooperation or to force the responding party to use TAR.”

Judge Peck, while acknowledging that he is “a judicial advocate for the use of TAR in appropriate cases”, also noted that he is also “a firm believer in the Sedona Principles, particularly Principle 6, which clearly provides that:

Responding parties are best situated to evaluate the procedures, methodologies, and technologies appropriate for preserving and producing their own electronically stored information.”

Judge Peck went on to state: “Under Sedona Principle 6, the City as the responding party is best situated to decide how to search for and produce ESI responsive to Hyles’ document requests. Hyles’ counsel candidly admitted at the conference that they have no authority to support their request to force the City to use TAR. The City can use the search method of its choice. If Hyles later demonstrates deficiencies in the City’s production, the City may have to re-do its search.  But that is not a basis for Court intervention at this stage of the case.”  As a result, Judge Peck denied the plaintiff’s application to force the defendants to use TAR.

So, what do you think?  Are you surprised by that ruling?  Please share any comments you might have or if you’d like to know more about a particular topic.

Don’t forget that next Wednesday at 1:00pm ET, ACEDS will be conducting a webinar panel discussion, titled How Automation is Revolutionizing eDiscovery, sponsored by CloudNine.  Our panel discussion will provide an overview of the eDiscovery automation technologies and we will really take a hard look at the technology and definition of TAR and the limitations associated with both.  This time, Mary Mack, Executive Director of ACEDS will be moderating and I will be one of the panelists, along with Bill Dimm, CEO of Hot Neuron and Bill Speros, Evidence Consulting Attorney with Speros & Associates, LLC.  Click on the link here to register.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine. eDiscovery Daily is made available by CloudNine solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Daily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Case Background

In this case involving various transfers from one entity to a related entity where the respondent determined that the transfers were disguised gifts to the petitioner’s owners and the petitioners asserted that the transfers were loans, the parties previously disputed the use of predictive coding for this case and, in September 2014 (covered by us here), Judge Buch ruled that “[p]etitioners may use predictive coding in responding to respondent’s discovery request. 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.”

At the outset of this ruling, Judge Buch noted that “[t]he parties are to be commended for working together to develop a predictive coding protocol from which they worked”.  As indicated by the parties’ joint status reports, the parties agreed to and followed a framework for producing the electronically stored information (ESI) using predictive coding: (1) restoring and processing backup tapes, (2) selecting and reviewing seed sets, (3) establishing and applying the predictive coding algorithm; and (4) reviewing and returning the production set

While the petitioners were restoring the first backup tape, the respondent requested that the petitioners conduct a Boolean search and provided petitioners with a list of 76 search terms for the petitioners to run against the processed data.  That search yielded over 406,000 documents, from which two 1,000 document samples were conducted and provided to the respondent for review.  After the model was run against the second 1,000 documents, the petitioners’ technical professionals reported that the model was not performing well, so the parties agreed that the petitioners would select an additional 1,000 documents that the algorithm had ranked high for likely relevancy and the respondent reviewed them as well.  The respondent declined to review one more validation sample of 1,000 documents when the petitioner’s technical professionals explained that the additional review would be unlikely to improve the model.

Ultimately, using the respondent’s selected recall rate of 95 percent, the petitioners ran the algorithm against the 406,000 documents to identify documents to produce (followed by a second algorithm to identify privileged materials) and, between January and March 2016, the petitioners delivered a production set of approximately 180,000 total documents on a portable device for the respondent to review and included a relevancy score for each document – ultimately, the respondent only found 5,796 to be responsive (barely over 3% of the production) and returned the rest.

On June 17, 2016, the respondent filed a motion to compel production of the documents identified in the Boolean search that were not produced in the production set (1,353 of 1,645 documents containing those terms they claimed were not produced), asserting that those documents were “highly likely to be relevant.”  Ten days later, the petitioner filed an objection to the respondent’s motion to compel, challenging the respondent’s calculations of documents that were incorrectly produced by noting that only 1,360 of documents actually contained those terms, that 440 of them had actually been produced and that many of the remaining documents predated or postdated the relevant time period.  They also argued that the documents were selected by the predictive coding algorithm based on selection criteria set by the respondent.

Judge’s Ruling

Judge Buch noted that “[r]espondent’s motion is predicated on two myths”: 1) the myth that “manual review by humans of large amounts of information is as accurate and complete as possible – perhaps even perfect – and constitutes the gold standard by which all searches should be measured”, and 2) the myth of a perfect response to the respondent’s discovery request, which the Tax Court Rules don’t require.  Judge Buch cited Rio Tinto where Judge Andrew Peck stated:

“One point must be stressed – it is inappropriate to hold TAR [technology assisted review] to a higher standard than keywords or manual review.  Doing so discourages parties from using TAR for fear of spending more in motion practice than the savings from using from using TAR for review.”

Stating that “[t]here is no question that petitioners satisfied our Rules when they responded using predictive coding”, Judge Buch denied the respondent’s Motion to Compel Production of Documents Containing Certain Terms.

So, what do you think?  If parties agree to the predictive coding process, should they accept the results no matter what?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine. eDiscovery Daily is made available by CloudNine solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Daily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.