Partner Gil Keteltas, co-editor of BakerHostetler’s Discovery Advocate blog, participated in a question-and-answer session with Senior Discovery Counsel for Recommind, Inc., Philip Favro. Keteltas’ responses appeared in a July 22, 2014, blog post on Recommind.com and addressed topics including FCRP Rule 26, proposed amendments to FCRP, predictive coding, and e-discovery challenges facing companies in 2014.
Editor’s Note: This blog post is joint submission with BakerHostetler’s Antitrust Advocate blog.
If your organization is facing the prospect of a merger investigation and your lawyers haven’t raised the prospect of technology-assisted document review (“TAR”), then maybe you should be talking with someone else.
What is TAR?
TAR, a relatively new entrant into the world of litigation and investigations, is an iterative process in which human subject matter experts (“SMEs”) interact with software and code small sets of documents. The computer takes into account the decisions of the subject matter experts and generates new sets of documents from which it thinks it will learn from the human decision makers. This process typically ends after a few thousand documents have been reviewed and the predictive coding tool concludes it can learn nothing more from the human reviewers. The predictive coding tool then extrapolates those judgments to the entire set of collected documents, and codes the documents as likely relevant or likely irrelevant.
This is not a “black box” or “set-it-and-forget-it” solution. Instead, the producing and requesting parties must first agree on protocols covering how the system will be trained, when training will end, and how the results will be audited. The parties will likely also discuss how transparent the training process will be to the requesting party. Will the requesting party participate in training? Will the responding party share its relevance decisions during the training process? How will privileged documents be handled? This may sound a bit more complicated than the traditional linear review, but TAR can provide efficiencies and consistency in return for that complication.
What are the benefits of TAR for merging parties facing the prospect of an investigation?
In a recent publication, the Department of Justice Antitrust Division’s Senior Litigation Counsel for Electronic Discovery, Tracy Greer, noted that the “use of TAR offers the promise of reducing the costs incurred by merging responding to Second Requests and the size the document productions received by the Division, without undermining the ability of the Division to conduct an appropriately thorough investigation.”
Greer offered several additional observations based on the Division’s negotiations of “TAR protocols in approximately a dozen instances.” Based on that experience, Greer found that “TAR produced smaller, more responsive document productions,” which “contained much more relevant information and less that obviously is not responsive.” Greer also felt that the Division staff benefited substantially and, based on reports from the producing parties, that the parties experienced “substantial time and cost savings” as well.
Greer went on to state that TAR provided additional opportunities to narrow party productions, including instances where the Division “encouraged parties using a TAR protocol to identify categories of documents that, while technically responsive to the Second Request, [were] not essential to resolving the competitive concerns at issue in the investigation.” Overall, Greer saw the use of TAR as “an opportunity to reduce further the size of the production,” which, in turn, saves the producing party money, and the producing party and the Division time.
But Greer also included an important caveat when it came to the validation of a TAR process. That is, the Division also consistently asked producing parties to “provide a statistically significant sample of nonresponsive documents to ensure that facially responsive documents were not excluded from the collection.” Why? To support the use of TAR, the Division was checking both the produced documents as well as samples of the data left behind, but the Division did except “documents coded as privileged” from that nonresponsive review.
So, why haven’t your lawyers raised the prospect of TAR with you? That is an excellent question.
If you have any questions regarding this topic, or would like to learn more about how our E-Discovery Advocacy and Management team can help you, please contact Gil Keteltas, national Co-leader of our E-Discovery Advocacy and Management team, email@example.com, or 202.861.1530, Karin Jenson, national Co-leader of our E-Discovery Advocacy and Management team, firstname.lastname@example.org, or 212.589.4266. If you would like to learn more about our Antitrust and Competition group, please contact Jonathan L. Lewis, email@example.com or 202.861.1557.
Last month, Edward Snowden provided the press a document describing “how Australian intelligence conducted surveillance of trade talks between Indonesia and the United States and, in the process, monitored communications between Indonesian officials and an American law firm retained by Indonesia for help with the trade dispute.”
Web-based email service providers may use automated processes to review email you send and receive. This may be done to look for spelling errors and spam. But it also may be done to target advertising based on the content of the email.
The terms of service of some cloud providers give the provider the right to access the content of material you create or store for purposes ranging from technical support to refining the cloud services they provide.
In this new digital world, is it reasonable to expect that a communication between client and lawyer for the purpose of obtaining legal advice is confidential (and, therefore, privileged)? The attorney-client privilege faces new tests with the advent of “the cloud” and other digital innovations. This was one of the topics covered in the Association of Certified E-Discovery Specialists’ program, “Inviting Scrutiny: The Impact of Digital Age Innovations on the Attorney-Client Privilege,” in which I participated with U.S. Magistrate Judge James Francis (SDNY) and Phil Favro of Recommind.
This week, after a seemingly endless year of construction, my family and I moved into our new, energy-efficient home. As I was in the kitchen unpacking, my daughter cried out, somewhat dramatically, “Mama, come here …. The thermostat is watching me…” Whereupon she proceeded to demonstrate this by waiting until the thermostat went dark and then walking toward it, causing it to awaken. Being a seasoned privacy and e-discovery lawyer, I responded with equal drama, “Of course dear … We are living in the age of the Internet of Things.” She was unimpressed with my knowledge. But it did get me to thinking. Isn’t e-discovery hard enough without worrying about the Internet of Things (“IoT”)?
The IoT seems to have popped up everywhere around us. Bob Gohn at Navigant has a great background piece on the IoT as well as a piece on the types of devices that make up the IoT and the security risks they create. But in layman’s terms, the IoT refers to all the devices that collect data through the use of sensors and connect to the internet that are not traditionally thought of as computing devices. It is exemplified not just by my nifty thermostat, but also by the FitBit, Google Glass, and even that smart parking meter that tells the meter reader when to come give you a ticket. The IoT is so pervasive in fact that the term is used interchangeably with the term the “Internet of Everything” and is expected to eclipse the market for traditional computing devices.
Certainly privacy and data security issues related to the IoT are legion. Given the ubiquity of the IoT, there is little doubt that it is only a matter of time until issues over devices that make up the IoT arise in regulatory enforcement proceedings and litigation. In fact, late last year, the FTC announced that it had its eye on the consumer risks presented by the IoT by filing a seven-page complaint against TRENDnet, a company that sells internet-connected cameras. The FTC complaint, which was settled just a few weeks ago by consent order, alleged that TRENDnet’s practices failed to provide reasonable security “to prevent unauthorized access to sensitive information, namely the live feeds from the IP cameras.” And just in case this enforcement activity wasn’t enough of a signal of its interest in the IoT, the FTC presented a workshop on the IoT, Internet of Things – Privacy and Security in a Connected World, late last year as well.
It’s a common refrain that, while courts have allowed the use of technology assisted review, no court has yet blessed the outcome of an imperfect technology assisted review process over the objection of another party. But dicta in Judge Denise Cote’s recent decision in FHFA v. HSBC North America Holdings Inc. (SDNY) (“HSBC“) gets darn close.
HSBC is one of a number of actions brought by the Federal Housing Finance Agency against financial institutions involved in the packaging, marketing and sale of residential mortgage-backed securities purchased by Fannie Mae and Freddie Mac. Judge Cote’s recent decision denied a request to reconsider her January 8th order barring the parties from using documents produced in separate litigation ongoing in California—the Countrywide litigation—unless those documents had also been produced in the New York action.
Among other things, Defendants sought to use a document produced in Countrywide to show that the productions in the New York litigation were incomplete. The Court rejected this argument in large part because it concluded diligence and good faith is required in responding to discovery requests, but perfection is not. Continue Reading
This post is a joint submission with BakerHostetler Data Privacy Monitor blog.
On a snowy Sixth Avenue this week, thousands of people packed the New York Hilton Midtown for the sensory overload that is LegalTech New York (#LTNY), the annual E-Discovery, privacy, and information governance bash.
And today, just hours after the massive conference closed, the E-Discovery conversation moves to Dallas for the third (and last) Advisory Committee for the Civil Rules hearing, at which the discussion will focus on whether to reinforce the proportionality provisions adopted eight years ago, and whether and how to clarify preservation obligations and the sanctions that attach to imperfect preservation.
But more on what happens in Dallas next week.
As a conference, LegalTech focused on many different aspects of technology’s intersection with the practice of law, but overarching it all was the specter of digital information—particularly, the safe management of client information (whether it be at the client, at the law firm, or in the “cloud”) and the provision and subsequent use of that information in the practice of law generally and in the context of litigation and related E-Discovery specifically.
This blog post is a joint submission with BakerHostetler’s Data Privacy Monitor blog.
Information is the lifeblood of businesses today. As the volume of data continues to grow exponentially, intelligent governance of information is essential for enterprises to survive and thrive. Data security concerns, privacy, compliance requirements and the costs of ediscovery all militate toward implementation of policies and procedures to effectively and efficiently manage information. In addition, the ability to utilize analytics and mine valuable information from large data sets has transformed data into an essential business intelligence resource. Amazon, for example, is well known for its success in using its own data to target advertising to customers based on their past purchases and purchases of similar customers, and to improve customer service operations.
But what is Information Governance? Information Governance establishes a consistent and logical framework for employees to handle data. It should create a high-level policy focused on enterprise-wide strategic and business goals. The process of developing an Information Governance policy should include all relevant stakeholders and take into account the enterprise’s organization and culture, legal/regulatory concerns, business operations, and technology. The policy must address the enterprise’s particular data challenges, such as retention of personal health information or managing streaming data from social media.
While recognizing the inherent value in some of the information being created and collected, an Information Governance policy must recognize that most data likely has no business value. Development and implementation of a solid defensible deletion plan therefore is a crucial component of Information Governance. Keeping everything simply doesn’t make sense, but deletion must be guided by legal considerations, such as the effect of legal holds, regulatory and compliance requirements and business concerns. In light of these high-stake considerations, the cost of keeping too or deleting too much information cannot be ignored.
The Information Governance policy also must address how retained information is managed. Redundancies should be eliminated as much as possible, and classification and organizational systems should be devised so that information can be easily and quickly retrieved.
It is essential for modern enterprises to get their data house in order to reduce costs and liabilities while also exploiting the benefits information now offers. Implementation of a solid Information Governance plan should be a high priority for all enterprises looking to thrive and succeed in today’s big data environment.
In some respects, 2013 seemed like a conversation between Vladimir and Estragon. Some commentators likened it to a simple, unified message that finally had E-Discovery practitioners, litigators in general, and affected clients speaking the same language; others feared that a continuation of the status quo meant simply that another year had passed without addressing the significant concerns associated with the over-preservation of data and the lack of judicial consistency.
Info Keeps on Growing
The truth, as was often the case, was somewhere in between. Certainly, more than “nothing” happened: by the end of 2013’s 525,600 minutes, 63 million additional people had joined LinkedIn (at a rate of two-per-second), 42% of whom regularly update their profiles; a comparatively paltry 25,228,800 hours of video was uploaded to YouTube; and an additional 3 billion web pages were created. And we cannot forget the users (and bots) who combined to send 52 trillion pieces of email. All of this contributed to an overall growth of enterprise-data by an astounding 40 to 60% over the course of 2013 (with an expected annual increase of 4,300% by 2020), which magnifies the importance of preservation and disposition decisions (or the lack thereof) – which is not to say no cases were decided in 2013, however.
There are Limits to your Search
The concerns about over-preservation and judicial consistency made some small strides in this rapidly increasing area of information storage, as courts continued to catch up with the practices followed several years ago. On one hand, absent a showing of relevance, courts will not always order discovery of social media in the context of “fishing expedition[s],” may decline to compel responses to “ultra-broad” requests and may uphold reasonable, proportional limits to the scope of discovery. In fact, a court might decline to sanction the routine deletion of text messages.On the other, the deletion of a Facebook account earned an adverse inference instruction, and auto-delete sanctions will continue into the foreseeable future. As far as case law trends in general go, e-discovery opinions were fairly evenly distributed across categories dealing with costs, preservation & spoliation, procedural issues, production, and sanctions.
This blog post is a joint submission with BakerHostetler’s Data Privacy Monitor blog.
During the final panel of Thomson Reuters’ 17th Annual eDiscovery & Information Governance in Practice Forum, Thomas Barnett, Ignatius Grande, and Sandra Rampersaud led a lively discussion on Managing Big Data, Dark Data, and Risk. And while the exchange incorporated Information Governance 101 principles such as the explosion of Social Media and the corresponding growth of new data year-over-year, an additional set of concerns was raised about “dusty” and “dark” data—data unknown to many organizations, and unmanaged by many more.
Dusty and Dark Data
Dusty data is data the organization – or someone within it – kind of knows about, but is still cloaked with mystery and obscured by time. Dark data is data organizations keep unknowingly, entirely lurking within the shadows. Put more simply, dusty data is the “known unknown;” dark data is the “unknown unknown.” But while there has at least been some scholarship done on dark data as a concept, dusty data has received a lot less press. Both are important, and both present risk; however, they present different risk, and should be treated differently.
You need both Responsibility and Authority to Drive Change?
The panel had limited time, and chose to consolidate both dusty and dark data into a single set of information when providing a framework for a pragmatic approach to a solution that would identify, classify, and manage the data within the context of information governance and legal holds. Their proposal, while complicated in practice, would rely on a clear mandate from a decision maker/stakeholder who would empower someone within the organization with both the responsibility to undertake the project, and the authority to implement change (e.g., assign resources and, perhaps most importantly, spend money where necessary). Continue Reading
Magistrate Judge Andrew J. Peck has observed that judicial understanding and resolution of ediscovery disputes can benefit from “bring your geek to court day” — where those knowledgeable about ESI issues in a case participate in court conferences. As we predicted, the Supreme Court isn’t yet ready for Bring Your Geek to the Supreme Court Day.
On its face, the petition for certiorari involved the appropriate standard for review of a decision that rejected recusal of Judge Peck from a case based on his publicly stated views on technology assisted review (TAR) and his participation in organizations, seminars and other events that cover the development of TAR. But the petition targeted what it described as “a global precedent in favor of predictive coding — a technique that had never before been adopted, and that is now (in large part thanks to Judge Peck) gaining footing.”
Does this denial of certiorari change the landscape for machine learning in litigation? No. In the time since Judge Peck issued his decision in Da Silva Moore, has the world reached agreement on how and when advanced search methods should be deployed in litigation? Perhaps not agreement, but certainly evolution in thinking, as evidenced by the June 2013 DESI V Workshop, Standards for Using Predictive Coding, Machine Learning, and Other Advanced Search and Review Methods in E-Discovery.
In many cases, which you do not and generally will not read about, parties are negotiating the terms of search and review in discovery. But standardization across dockets and technologies presents more complicated questions, as Jason Baron noted in his report on the DESI V Workshop.
But Bring Your Geek to the Supreme Court Day is off the calendar, for now.