Lighthouse Blog

Since Judge Andrew Peck’s ruling over nine years ago in Da Silva Moore v. Publicis Groupe & MSL Group, the use of Technology-Assisted Review (TAR) for managing review in eDiscovery has been court approved. Yet many lawyers and legal professionals still don’t use machine learning (which, for many, is synonymous with TAR) in litigation. In the eDiscovery Today 2021 State of the Industry report, only 31.1% of respondents said they use TAR in all or most of their cases; 32.8% of respondents said they use it in very few or none of their cases. So, why don’t more lawyers use TAR?Transparency and TAROne possible reason that lawyers avoid the use of TAR is that requesting parties often demand more transparency with a TAR process than they do with a process involving keyword search and manual review. Judge Peck (retired magistrate judge and now Senior Counsel with DLA Piper) stated in the eDiscovery Today State of the Industry report: “Part of the problem remains requesting parties that seek such extensive involvement in the process and overly complex verification that responding parties are discouraged from using TAR.”In the article Predictive Coding: Can It Get A Break?, author Gareth Evans, a partner at Redgrave, states: “Probably the greatest impediment to the use of predictive coding has been the argument that the party seeking to use it should agree to share its coding decisions on the documents used to train the predictive coding model, including providing to the opposing party the irrelevant documents in the training sets.”Lawyer training vs. “black box” technologyWhy do lawyers expect that they are entitled to more transparency with TAR? Perhaps a better question might be: why do they demand less transparency for keyword search and manual review? One reason might lie in the education and training that they receive to become lawyers. Many lawyers cut their teeth on the keyword search used for resources like Westlaw and Lexis. Consequently, keyword search is part of their experience and they feel comfortable using it.Those same lawyers see keyword search and manual review for discovery as an extension of what they learned in law school. But it’s not. Search (aka “information retrieval”) is an expertise. Effective keyword search for discovery purposes is an iterative process that requires testing and verification of the search result set and the discard pile to confirm that the scope of the search wasn’t too narrowly focused. The end goal is to construct a search with both high recall and high precision; to identify those documents potentially responsive to a production request without also capturing non-responsive information, which can significantly increase review costs. This is very different from the goal of identifying a handful of documents that can assist in a case precedents argument.With regard to TAR, many lawyers still see the technology as a “black box” that they don’t understand. So, when the other side proposes using TAR, they want a lot more transparency about the particular TAR process to be used. It’s simply human nature to ask more questions about things we don’t understand. But, truth be told, lawyers should probably be just as vigilant in seeking information about the opposing’s use of keyword search as they are when TAR is the approach being proposed.TAR technology in daily livesWhat many lawyers may not realize is that they’re already using the type of technology associated with TAR elsewhere in their lives — albeit with a different goal and lower stakes than in a legal case. TAR is based on a supervised machine learning algorithm, where the algorithm learns to deliver similar content based on human feedback. Choices we make in Amazon, Spotify, and Netflix influence what those platforms deliver to us as other choices we might want to see in terms of items to buy, songs to listen to or movies to watch. The process of “training” the algorithms that drive these platforms makes them more useful to us — just as the feedback we provide during a predictive coding process helps train the algorithm to identify documents most likely to be responsive to the case.ConclusionWhat should lawyers do when opposing counsel makes transparency demands regarding TAR processes to be used? Certainly, cooperation and discussion of the protocol as soon as possible — such as the Rule 26(f) “meet and confer” between the parties — can help everyone get “on the same page” about what information can or should be shared, no matter what approach is proposed.However, if the parties can’t reach an accord regarding TAR transparency, perhaps another case ruling by Judge Peck — Hyles v. New York City — can be instructive here, where Judge Peck cited Sedona Principle 6. This principle states: “Responding parties are best situated to evaluate the procedures, methodologies, and technologies appropriate for preserving and producing their own electronically stored information.” Ironically, in Hyles, the requesting party was trying to force the responding party to use TAR, but Judge Peck, despite being an acknowledged “judicial advocate for the use of TAR in appropriate cases” denied the requesting party’s motion in that case. Transparency demands from requesting parties shouldn’t deter you from realizing the potential efficiency gains and cost savings resulting from an effective TAR process.For more information on H5 Litigation Services, including review for production with the H5 unique TAR as a Service, click here.ediscovery-reviewediscovery-reviewblog; tar; litigation; technology-assisted-review; predictive-coding; ediscovery; machine-learningmitch montoya

It’s no secret that big data can mean big challenges in the eDiscovery world. Data volumes and sources are exploding year after year, in part due to a global shift to digital forms of communication in working environments (think emails, chat messages, and cloud-based collaboration tools vs. phone calls, in-person meetings, and paper memorandums, etc.) as well as the rise of the Cloud (which provides cheaper, more flexible, and virtually limitless data storage capabilities).This means that with every new litigation or investigation requiring discovery, counsel must collect massive amounts of potentially relevant digital evidence, host it, process it, identify the relevant information within it (as well as pinpoint any sensitive or protected information within that relevant data) and then produce that relevant data to the opposing side. Traditionally, this process then starts all over again with the next litigation – often beginning back at square one in a vacuum by collecting the exact same data for the new matter, without any of the insights or attorney work product gained from the previous matter.This endless cycle is not sustainable as data volumes continue to grow exponentially. Fortunately, just as advances in technology have led to increasing data volumes, advances in artificial intelligence (AI) technology can help tackle big data challenges. Newer analytics technology can now use multiple algorithms to analyze millions of data points across an organization’s entire legal portfolio (including metadata, text, past attorney work product, etc.) and provide counsel with insights that can improve efficiency and curb the endless cycle of re-inventing the wheel on each new matter. In this post, I’ll outline the four main challenges big data can pose in an eDiscovery environment (also called “The Four Vs”) and explain how cutting-edge big data analytics tools can help tackle them.The “Four Vs” of Big Data Challenges in eDiscovery 1. The volume, or scale of dataAs noted above, a primary challenge in matters involving discovery is the sheer amount of data generated by employees and organizations as a whole. For reference, most companies in the U.S. currently have at least 100 terabytes of data stored, and it is estimated that by 2025, worldwide data will grow 61 percent to 175 zettabytes.As organizations and individuals create more data, data volumes for even routine or small eDiscovery matters are exploding in correlation. Unfortunately, court discovery deadlines and opposing counsel production expectations rarely adjust to accommodate this ever-growing surge in data. This can put organizations and outside counsel in an impossible position if they don’t have a defensible and efficient method to cull irrelevant data and/or accurately identify important categories of data within large, complex data sets. Being forced to manually review vast amounts of information within an unrealistic time period can quickly become a pressure cooker for critical mistakes – where review teams miss important information within a dataset and thereby either produce damaging or sensitive information to the opposing side (e.g., attorney-client privilege, protected health information, trade secrets, non-relevant information, etc.) or in the inverse, fail to find and produce requested relevant information.To overcome this challenge, counsel (both in-house and outside counsel) need better ways to retain and analyze data – which is exactly where newer AI-enabled analytics technology (which can better manage large volumes of data) can help. The AI-based analytics technology being built right now is developed for scale, meaning new technology can handle large caseloads, easily add data, and create feedback loops that run in real time. Each document that is reviewed feeds into the algorithm to make the analysis even more precise moving forward. This differs from older analytics platforms, which were not engineered to meet the challenges of data volumes today – resulting in review delays or worse, inaccurate output that leads to critical mistakes.2. The variety, or different forms of dataIn addition to the volume of data increasing today, the diversity of data sources is also increasing. This also presents significant challenges as technologists and attorneys continually work to learn how to process, search, and produce newer and increasingly complicated cloud-based data sources. The good news is that advanced analytics platforms can also help manage new data types in an efficient and cost-effective manner. Some newer AI-based analytics platforms can provide a holistic view of an organization’s entire legal data portfolio and identify broad trends and insights – inclusive of every variety of data present within it. These insights can help reduce cost and risk and sometimes enable organizations to upgrade their entire eDiscovery program. A holistic view of organizational data can also be helpful for outside counsel because it also enables better and more strategic legal decisions for individual matters and investigations.3. The velocity, or the speed of dataWithin eDiscovery, the velocity of data not only refers to the speed at which new data is generated, but also the speed at which data can be processed and analyzed. With smaller data volumes, it was manageable to put all collected data into a database and analyze it later. However, as data volumes increase, this method is expensive, time consuming, and may lead to errors and data gaps. Once again, a big data analytics product can help overcome this challenge because it is capable of rapidly processing and analyzing iterative volumes of collected data on an ongoing basis. By processing data into a big data analytics platform at the outset of a matter, counsel can quickly gain insights into that data, identifying relevant information and potential data gaps much earlier in the processes. In turn, this can mean lower data hosting costs as objectively non-responsive data can be jettisoned prior to data hosting. The ability of big data analytics platforms to support the velocity of data change also enables counsel and reviewers to be more agile and evolve alongside the constantly changing landscape of the discovery itself (e.g., changes in scope, custodians, responsive criteria, court deadlines).4. The veracity, or uncertainty of dataWithin the eDiscovery realm, the veracity of data refers to the quality of the data (i.e., whether the data that a party collects, processes, and produces is accurate and defensible and will satisfy a discovery request or subpoena). The veracity of the data produced to the opposing side in a litigation or investigation is therefore of the utmost importance, which is why data quality control steps are key at every discovery stage. At the preservation and collection stages, counsel must verify which custodians and data sources may have relevant information. Once that data is collected and processed, the data must then be checked again for accuracy to ensure that the collection and processing were performed correctly and there is no missing data. Then, as data is culled, reviewed, and prepared for production, multiple quality control steps must take place to ensure that the data slated to be produced is relevant to the discovery request and categorized correctly with all sensitive information appropriately identified and handled. As data volumes grow, ensuring the veracity of data only becomes more daunting.Thankfully, big data analytics technology can also help safeguard the veracity of data. Cutting-edge AI technology can provide a big-picture view of an organization’s entire legal portfolio, enabling counsel to see which custodians and data sources contain data that is consistently produced as relevant (or, in the alternative, has never been produced as relevant) across all matters. It can also help identify missing data by providing counsel with a holistic view of what was collected in past matters from data sources. AI-based analytics tools can also help ensure data veracity on the review side within a single matter by identifying the inevitable inconsistencies that happen when humans review and categorize documents within large volumes of data (i.e., one reviewer may categorize a document differently than another reviewer who reviewed an identical or very similar document, leading to inconsistent work product). Newer analytics technology can more efficiently and accurately identify those inconsistencies during the review process so that they can be remedied early on before they cause problems. Big Data Analytics-Based MethodologiesAs shown above, AI-based big data analytics platforms can help counsel manage growing data volumes in eDiscovery.For a more in-depth look at how a cutting-edge analytics platform and big data methodology can be applied to every step of the eDiscovery process in a real-world environment, please see Lighthouse’s white paper titled “The Challenge with Big Data.” And, if you are interested in this topic or would like to talk about big data and analytics, feel free to reach out to me at KSobylak@lighthouseglobal.com.ai-and-analytics; ediscovery-reviewcloud, analytics, ai-big-data, ediscovery-process, prism, blog, ai-and-analytics, ediscovery-reviewcloud; analytics; ai-big-data; ediscovery-process; prism; blogkarl sobylak

By Steven L. Clark, E-Discovery and Litigation Support Director, Dentons and John Del Piero, Vice President, LighthouseWhether your firm is just beginning to consider a move to a managed service eDiscovery model or you’re a managed service veteran, it is imperative to understand what makes this type of eDiscovery program model successful. After all, if you don’t know how to measure success, it will be difficult to know what to look for when selecting a provider, and equally as hard to monitor the quality of the services provided once you have selected one.However, measuring success can be complex. There are many different metrics that could be used to measure success and each may be of a varying level of importance to different firm stakeholders, as the priorities of these stakeholders will be determined by their particular role and focus. However, a successful managed service partnership can be based on a foundation of six core pillars. These pillars can be used as guideposts when evaluating whether a managed service partner will truly add value to a law firm’s eDiscovery process.Pillar 1: Access to Best-of-Breed Technology and Teams of Experts to Help Leverage ItA managed service partnership should always make a law firm (and its clients) feel like the best eDiscovery technology is right at their fingertips. But more than that, a successful managed service relationship should enable a law firm to stay technologically agile, while lowering technology costs.For example, if an eDiscovery tool or platform becomes obsolete or outdated, the firm’s managed service partner should be able to quickly move the firm to better technology, with little cost to the firm. In other words, in a successful managed service partnership, gone are the days where a litigation support team was stuck using an obsolete platform simply because the law firm purchased an enterprise license for that technology. Rather, the managed service partner should bear the cost burden of leveraging continuously evolving technology because the partner can easily spread that technological risk across its client base. In assuming this burden, the managed services partner ultimately provides law firms much greater flexibility in terms of leveraging the most appropriate technology to meet their clients’ needs.In addition to simply providing access to the best technology, a successful managed service partnership should also provide teams of experts who are wholly dedicated to helping law firms leverage that technology for optimal impact. These experts should be continuously vetting new applications and technology upgrades, enabling litigation support teams to stay up to date on evolving applications and tools. These teams will also be able to create and test customized workflows that enable law firms to handle how data flows through technically robust collaborative platforms like Microsoft Teams or Slack, as well as keep firms apprised of any updates to cloud-based platforms that may affect existing eDiscovery workflows.This type of devoted technological expertise and guidance can provide firms a significant competitive boost, as internal litigation support teams rarely have the resources available to devote staff solely to testing new technology and building customized workflows.Pillar 2: A Scalable and More Diversified eDiscovery Team In comparison to a traditional law firm litigation support team which, naturally, is somewhat static in size, a successful managed service relationship allows law firm teams to quickly and seamlessly scale up or down, depending on case needs. For example, when a large matter comes in, a managed service provider should have the ability to quickly pull a project manager in to help manage the case while the internal law firm team still retains day-to-day control of the matter. This alleviates the firm from having to choose between hiring additional staff (only to be faced with too big of a team once the larger matter ends) or outsourcing the case to an external, inflexible eDiscovery provider (where the firm may be unable to retain full control of the matter and will undoubtedly have to adapt to different processes and workflows).A managed service partner’s bench should also be deep, allowing a law firm to pull from a diverse pool of expertise. Whether the law firm needs a review workflow expert or a processing expert, an analytics expert or a migration and normalization expert, a quality managed service provider should be able to swiftly provide someone who knows the teams involved and has the qualifications and technological background to ensure that all stakeholders trust their expertise and guidance.Pillar 3: eDiscovery Expertise 24/7/365A managed service provider should not only provide law firms with top-notch eDiscovery expertise but also provide access to that expertise whenever it is needed. Unfortunately, most litigation support teams are all too familiar with the fact that eDiscovery is almost never a 9 to 5 job. The nature of litigation today means that a Monday production deadline involving a terabyte of data may be doled out by a judge on a Friday morning, or that data for a pressing production may arrive at 9:00 p.m. The list of eDiscovery off-hour emergencies is somewhat endless.Unfortunately, most internal litigation support teams at law firms are located in one geographic area (and therefore, one time zone), meaning that even when internal teams have the required expertise, they may not have those resources available when they’re needed.A quality managed service partner, however, will be able to provide resources whenever they are needed because it can structure its hiring and team assignments with team members located across multiple time zones. Access to full-time eDiscovery expertise and coverage enables law firms to swiftly handle any eDiscovery task with ease, with no permanent increase in staffing overhead.Pillar 4: Less Talent Acquisition RiskA successful managed service relationship should also significantly lower law firm risk related to talent acquisition and training. While hiring in today’s job climate may seem like a simple task, the cost of sufficiently vetting candidates and then providing the appropriate training can be incredibly time consuming and expensive.If law firm vetting misses a candidate red flag or even if a candidate just needs more training than expected, staffing costs and time expenses can skyrocket even further. For example, the task of having to substantially re-train a new hire from the ground up can take up the valuable time of other internal experts. In this way, even the most routine hire can often slow productivity and lower the morale of the entire internal team (at least in the short term) until the hire can be fully integrated into the department’s daily workflow.In a successful managed service relationship, however, the law firm can transfer those types of hiring and training risks directly to the provider. The managed service provider is already continuously evaluating, vetting, and training talent across different geographies in order to hire the best eDiscovery experts. Law firms can simply reap the benefit of this process by partnering with the service provider and leveraging that talent once the vetting and training process has been completed.Pillar 5: Lower Staffing Overhead To put it simply, all of the above means that moving to a managed service model should allow a law firm to significantly lower its overhead costs related to staffing and management. In addition to taking on the hiring risks, a managed service provider should also take on much of the overhead related to maintaining staff. From payroll, to benefits, to overtime costs, a quality managed service provider handles those costs and time expenses for their own on-staff experts, leaving the law firm free to reap the benefits of on-demand expertise without the staffing overhead costs.Pillar 6: Better Billing MechanicsMost law firms are not set up to bill eDiscovery services efficiently. eDiscovery billing has evolved over the last few years, and a quality managed service provider should be following suit and offering simplified, predictable cost models in order for law firms to pass that predictability on to their clients. This kind of simplified pricing enables all parties to understand exactly how much they are going to spend for the eDiscovery services provided. However, this billing structure differs significantly from the way traditional legal work is billed out, and most law firms’ billing infrastructures have not evolved to offer the same level of predictability or cost certainty. This is where a quality managed service provider can provide another benefit, by heavily investing its own resources into building out automated reporting, ticketing, and billing systems that can generate proformas and integrate into the firm’s existing billing systems.If a managed service provider can take care of these billing tasks, law firm teams can spend more time in furtherance of client work, rather than devoting resources into eDiscovery billing metrics and workarounds.SummaryAccess to and expertise in appropriate technology, flexible staffing models, lower overhead, and simplified pricing are the six pillars of a successful managed service partnership in a law firm setting. When all six of these pillars are in place, the managed service partnership will result in more satisfied internal and external law firm customers and an increasing caseload year after year. For more information or to discuss this topic, reach out to us at info@lighthouseglobal.com.legal-operations; ediscovery-reviewmanaged-services, blog, law-firm, legal-operations, ediscovery-reviewmanaged-services; blog; law-firmlighthouse

Most of you are pretty familiar with using website chatbots in your daily lives – whether to assist in your online banking or to help with a product issue. But what if you went to report sexual harassment at work and you were greeted by a chatbot? That may seem a little unusual, however, there are a couple of advantages to this approach, including a better customer service experience for internal customers and allowing the compliance professionals to take on more complex work. For several years the legal and compliance industry discussions around chatbots have focused on how law firms can use chatbots. In this blog, I will focus on three ways in-house legal and compliance departments should use them to their advantage.1. As a legal intake tool.A common challenge for legal departments is how to intake matters and manage the work in the legal department. Legal operations teams are always looking for ways to understand what people are doing and how to make the process more efficient. There is a lot of discussion on how forms and/or workflow tools can be leveraged to solve this issue – and they are very helpful – but you can take this one step further with a chatbot. When someone inside your organization comes to the legal team, you can have a chatbot gather basic, or even more detailed, information about what they need. You can train a chatbot to understand the category of their need – advice, contract, patent, litigation, eDiscovery – and then take them through a series of questions to better understand the need. You can then even have the request routed through your workflow tool so it gets assigned to the right person (e.g., assigned to an attorney, a paralegal, or an eDiscovery project manager). As your chatbot gets familiar with the questions, you can have it ask deeper questions and take the request even further.2. To answer common legal questions.Legal departments tend to run lean. As a former general counsel who still speaks with a lot of legal department leaders, I know these leaders are always looking for ways to do more with less (or the same). They want to ensure their teams are spending time on substantive legal issues and not answering common questions that come up and can be handled differently. For example, answering questions about where to find the sexual harassment training or how to send over or sign a standard NDA, are questions that come into the legal department and lawyers spend their time answering them. These questions could easily be answered by a chatbot trained with common questions. This would provide a better user experience because the information is shared instantaneously with the user and it also frees up time for legal resources to spend their time on more unique issues. Finally, legal team members also feel more productive and engaged because their time isn’t being spent on more administrative tasks!3. In place of a hotline.This is one of the more unique use cases I have heard recently but it makes a lot of sense. Compliance hotlines work well because of the anonymity available but there is not an opportunity to share information back with the person reporting. For example, the person reporting an incident may want to know what the next steps might be, where they can find a certain policy, or where they can find additional resources. None of that is available via a hotline or even a form. With a chatbot, however, you can keep the anonymity but mimic a more personal conversation where additional resources can be shared. As shared on the Women in Compliance podcast, one organization has trained chatbots to be their first line of intake and support on sexual harassment complaints. The internal response has been very positive.legal-operationscompliance-and-investigations, legal-ops, blog, legal, legal-operations,compliance-and-investigations; legal-ops; blog; legallighthouse

Whether it’s called DIY eDiscovery, SaaS eDiscovery, or self-service, spectra eDiscovery, one thing is clear—everyone in the legal world is interested in putting today’s technologies to work for them to get more done with less. It’s a smart move, given that many legal teams are facing an imbalance between needs and resources. As in-house legal budgets are being slashed, actual workloads are increasing.Now more than ever, legal teams need to ensure they’re choosing and using the right tools to effectively manage dynamic caseloads—a future-ready solution capable of supporting a broad range of case types at scale. Given the variety of options on the market, it’s understandable there’s some uncertainty about what to pursue, let alone what to avoid. Below, I have outlined guidance to help your legal team navigate the top three potential pitfalls encountered when seeking a self-service, spectra eDiscovery solution.1. Easy vs. PowerfulThere are a lot of eDiscovery solutions out there making bold promises, but many still force users to choose between ease of use and full functionality. While a platform may be simple to learn and navigate, it may fail to offer advanced features like AI-driven analysis and search, for example.Think of it like the early days of cell phones, when we were forced to choose between a classic brick-style device or a new-to-market smartphone. Older phones were easy to use, offering familiar capabilities like calling and text exchange, while newer smartphones provided impressive, previously unknown functionalities but came with a learning curve. With the advancement of technology, today’s device buyers can truly have it all at hand—a feature-rich mobile phone delivered in an intuitive user experience.The same is true for dynamic eDiscovery solutions. You shouldn’t have to choose between power and simplicity. Any solution your team considers should be capable of delivering best-in-class technology over one simple, single-pane interface.2. Short-Term Thinking vs. Long-Term Gains As organizations move to the seemingly unlimited data storage capacities of cloud-based platforms and tools, legal teams are facing a landslide of data. Even the smallest internal investigation may now involve hundreds of thousands of documents. And with remote working being the new global norm, this trend will only continue to grow. Legal teams require eDiscovery tools that are capable of scaling to meet any data demand at every stage of the eDiscovery process.When evaluating an eDiscovery solution, keep the future in mind. The solution you select should be capable of managing even the most complex case using AI and advanced analytics—intelligent functionality that will allow your team to efficiently cull data and gain insights across a wide variety of cases. Newer AI technology can aggregate data collected in the past and analyze its use and coding in previous matters—information that can help your team make data-driven decisions about which custodians and data sources contain relevant information before collection. It also offers the ability to re-use past attorney work product, allowing you to save valuable time by immediately identifying junk data, attorney-client privilege, and other sensitive information.3. Innovation vs. UpkeepThanks to the DIY eDiscovery revolution, your organization no longer has to devote budget and IT resources to upkeeping a myriad of hardware and software licenses or building a data security program to support that technology. Seek a trusted solution provider that can take on that burden with development and security programs (with the requisite certifications and attestations to prove it). This should include routine technology assessment and testing, as well as using an approach that doesn’t disrupt your ongoing work.As you’re asked to do more with less, the right cloud-based eDiscovery platform can ensure your team is able to meet the challenge. By avoiding the above pitfalls, you’ll end up with a solution that’s able to stand up against today’s most complex caseloads, with powerful features designed to improve workflow efficiency, provide valuable insights, and support more effective eDiscovery outcomes.If you’re interested in moving to a DIY eDiscovery solution, check out my previous blog series on self-service, spectra eDiscovery for corporations, including how to select a self-service, spectra eDiscovery platform, tips for self-service, spectra eDiscovery implementation, and how self-service, spectra eDiscovery can make in-house counsel life easier. ediscovery-review; ai-and-analyticsself-service, spectra, ediscovery-process, corporation, prism, blog, spectra, corporate, ediscovery-review, ai-and-analyticsself-service, spectra; ediscovery-process; corporation; prism; blog; spectra; corporatelighthouse

Ever since ABA Model Rule of Professional Conduct 1.1 [1] was modified in 2012 to include an ethical obligation for attorneys to “keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology [2]” (emphasis added), attorneys in almost every state have had a duty to stay abreast of how technology can both help and harm clients. In other words, most attorneys practicing law in the United States have an ethical obligation to not only understand the risks created by the technology we use in our practice (think data breaches, data security, etc.), but also to keep abreast of technology that may benefit our practice.Nowhere is this obligation more implicated than within the eDiscovery realm. We live in a digital world and our communications and workplaces reflect that. Almost any discovery request today will involve preserving, collecting, reviewing, and producing electronically stored information (ESI) – emails, text messages, video footage, Word documents, Excels, PowerPoints, social media posts, collaboration tool data – the list is endless. To respond to ESI discovery requests, attorneys need to use (or in many cases, hire someone who can use) technology for every step of the eDiscovery process – from preservation to production. Under Model Rule 1.1, that means that we must stay abreast of that technology, as well as any other technology that may be beneficial to completing those tasks more effectively for our clients (whether we are providing legal advice to an organization as in-house counsel or externally through a law firm).In this post, I posit that in the very near future, this ethical obligation should include a duty to understand and evaluate the benefits of leveraging Artificial Intelligence (AI) during almost any eDiscovery matter, for a variety of different use cases.AI in eDiscoveryFirst, let’s level set by defining the type of technology I’m referring to when I use the term “AI,” as well as take a brief look at how AI technology is currently being used within the eDiscovery space. Broadly speaking, AI refers to the capability of a machine to imitate intelligent human behavior. Within eDiscovery, the term is often also used broadly to refer to any technology that can perform document review tasks that would normally require human analysis and/or review.There is a wide range of AI technology that can help perform document review tasks. These include everything from older forms of machine learning technology that can analyze the text of a document and compare it to the decisions made about that document by a human to predict what the human decision would be on other documents to newer generations of analytics technology that can analyze metadata and language used within documents to identify complicated concepts, like the sentiment and tone of the author. This broad spectrum of technology can be incredibly beneficial in a number of important document review use cases – the most common of which I have outlined below: Culling Data - One of the most common use cases for AI technology within eDiscovery is leveraging it to identify documents that are relevant to the discovery request and need to be produced. Or, conversely, identify documents that are irrelevant to the matter at hand and do not need to be produced. AI technology is especially proficient at identifying documents that are highly unlikely to be responsive to the discovery request. In turn, this helps attorneys and legal technologists “cull” datasets, essentially eliminating the need to have a human review every document in the dataset. Newer AI technology is also better at identifying documents that would never be responsive to any document request (i.e., “junk” documents) so that these documents can be quickly removed from the review queue. More advanced AI technology can do this by aggregating previously collected data from within an organization as well as the attorney decisions made about that data, and then use advanced algorithms to analyze the language, text, metadata, and previous attorney decisions to identify objectively non-responsive junk documents that are pulled into discovery request collections time and time again. Prioritizing and Categorizing Data - Apart from culling data, AI can also be used to simply make human review more efficient. Advanced AI technology can be used to identify specific concepts and issues that attorneys are looking for within a dataset and group them to expedite and prioritize attorney review. For example, if a litigation involves an employee accused of stealing company information, advanced AI technology can analyze all the employee’s communications and digital activities and identify any anomalies, such as an activity that occurred during abnormal work hours or communications with other employees with whom they normally would not have reason to interact. The machine can then group those documents so that attorneys can review them first. This identification and prioritization can be critical in evaluating the matter as a whole, as well as helping attorneys make better strategic decisions about the matter. Review prioritization can also simply help meet court-imposed production deadlines on time by enabling human reviewers to focus on data that can go out the door quickly (i.e., documents that the machine identified as highly likely to be responsive but also highly unlikely to involve issues that would require more in-depth human review like privilege, confidentiality, etc.). Identifying Sensitive Information - On the same note, AI technology is now more adept at identifying issues that usually require more in-depth human review. Newer AI technology that uses advanced Natural Language Processing (NLP) and analyzes both the metadata and text of a document is much better at identifying documents that contain sensitive information, like attorney-client privileged communications, company trade secrets, or personally identifiable information (PII). This is because more advanced NLP can take context into account and, therefore, more accurately identify when an internal attorney is chatting with other employees over email about the company fantasy football rankings vs. when they are providing actual legal advice about a work-related matter. It can do this by analyzing not only the language being used within the data, but also how attorneys are using that language and with whom. In turn, this helps attorneys conducting eDiscovery reviews prioritize documents for review, expedite productions, and protect privileged information.Attorneys’ Ethical Obligation to Consider the Benefits of AI in eDiscovery The benefits of AI in eDiscovery should now be clear. It is already infeasible to conduct a solely human linear review of terabytes of data without the help of AI technology to cull and/or prioritize data. A review of that amount of data (performed by humans reviewing one document at a time) can require months and even years, a virtual army of human reviewers (all being paid at an hourly rate), as well as the training, resources, and technology necessary for those reviewers to perform the work proficiently. Because of this, AI technology (via technology assisted review (TAR)) has been widely accepted by courts and used by counsel to cull and prioritize large sets for almost a decade.However, while big datasets involving terabytes of data were once the outliers in the eDiscovery world, they are now quickly becoming the norm for organizations and litigations of all sizes due to exploding data volumes. To put the growing size of organizational data in context, the total volume of data being generated and consumed has increased from 33 zettabytes worldwide in 2018 to a predicted 175 zettabytes in 2025[3]. This means that soon, even the smallest litigation or investigation may involve terabytes of data to review. In turn, that means that AI technology will be critical for almost any litigation involving a discovery component.And that means that we as attorneys will have an ethical duty to keep abreast of AI technology to competently represent our clients in matters involving eDiscovery. As we have seen above, there is just no way to conduct massive document reviews without the help of AI technology. Moreover, the imperative task of protecting sensitive client data like attorney-client privilege, trade secret information, and PII (which all can be hidden and hard to find amongst massive amounts of data) also benefits from leveraging AI technology. If there is technology readily available that can lower attorney costs and client risk, while ensuring a more consistent and accurate work product, we have a duty to our clients to stay aware of that technology and understand how and when to leverage it.But this ethical obligation should not scare us as attorneys and it doesn’t mean that every attorney will need to become a data scientist in order to ethically practice law in the future. Rather, it just means that we, as attorneys, will just need to develop a baseline knowledge of AI technology when conducting eDiscovery so that we can effectively evaluate when and how to leverage it for our clients, as well as when and how to partner with appropriate eDiscovery providers that can provide the requisite training and assist with leveraging the best technology for each eDiscovery task.ConclusionAs attorneys, we have all adapted to new technology as our world and our clients have evolved. In the last decade or so, we have moved from Xerox and fax machines to e-filings and Zoom court hearings. The same ethic that drives us to evolve with our clients and competently represent them to the best of our ability will continue to drive us to stay abreast of the exciting changes happening around AI technology within the eDiscovery space.To discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com.‍[1] “Client-Lawyer Relationship: A lawyer shall provide competent representation to a client. Competent representation requires the legal knowledge, skill, thoroughness and preparation reasonably necessary for the representation.” ABA Model Rules of Professional Conduct, Rule 1.1.[2] See Comment 8, Model Rules of Professional Conduct Rule 1.1 (Competence)[3] Reinsel, David; Gantz, John; Rydning, John. “The Digitization of the World From Edge to Core.” November 2018. Retrieved from https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf. An IDC White Paper, Sponsored by SEAGATE.ai-and-analyticsanalytics, ai-big-data, ediscovery-process, red-flag-reporting, departing-onboarding-employee, prism, blog, focus-discovery, ai-and-analytics,analytics; ai-big-data; ediscovery-process; red-flag-reporting; departing-onboarding-employee; prism; blog; focus-discoverysarah moran

Legal departments tend to run fairly lean. This means relying on external parties to accomplish any task is the norm. But when you are managing dozens of outside counsel on different matters, it can be nearly impossible to keep abreast of email traffic, calendars, and the status of any given task. Thankfully with a little bit of technology and some organization, this issue can be solved. This blog will share some tips on how other legal departments have solved this challenge.Select a technology platform to support organization and collaboration. The technology should allow internal and external parties to edit documents, view and manage calendars, organize task lists, and make comments and/or send messages to each other. There are many technologies that organizations use, such as Microsoft Teams or Google Workspace, that work well for this type of collaboration internally, but are not necessarily set up for external collaboration. With some additional work, you can also set these tools up for external collaboration. However, given all the privacy and data management considerations for internal use, one can imagine how high the hurdles are to set this up for external use. If you are facing those hurdles, there are several third-party technologies, such as Joinder and HighQ, that work well for external collaboration. These third-party cloud technologies are fairly low cost and quick to implement. The most important thing here is to choose a single platform. You want to make sure that you are able to minimize switching platforms with every new matter and/or outside counsel. Imagine the ease with which you can get an overview of all your legal work if you can log in to one platform and see your litigation eDiscovery deadlines, patent filing deadlines, and third-party subpoena response deadlines. You can then seamlessly edit the associated documents and assign a task to the next reviewer. You can see how selecting a single platform provides greater visibility and efficiency.Ensure each third party has a person responsible for maintaining the records inside the shared technology. Although you will likely have multiple people working on any given matter, you want to make sure there is at least one person from each third party who is responsible for updating the system. This should be someone knowledgeable about the matter, the deadlines, and the tasks. This should also be someone who is highly organized and comfortable with the technology.Agree upon a common organizational structure. The hardest thing about managing hundreds of matters is staying organized across all of them. If you choose a way to organize that remains consistent, it makes it much easier to find what you are looking for quickly. For example, you may choose to folder documents and tasks by matter type or by the department of origination. Either way, make sure it is a structure that makes sense across your legal portfolio. Here are some considerations to ponder when deciding how to name your files.Write the above into your outside counsel guidelines. A third-party collaboration tool and the organizational system are only as good as the adoption. By writing a requirement to keep it updated into your outside counsel guidelines, you are increasing the chances of success. Here is some sample text for your use:[Company name] uses [software name] as its third-party collaboration tool and asks that each of its outside counsel use [software name] for all work on the matter. On at least a weekly basis, outside counsel shall update [software name] with important dates in the matter, an updated list of tasks in the matter, and any final versions of key documents in the matter.The benefits of having all your legal documents in one platform increase over time. You create a system of records that can be referenced at any time. I hope that these tips will help you implement a solution for third-party collaboration so you can reduce the time you spend searching your email for the last version of the contract.legal-operationsediscovery-process, legal-ops, blog, legal-operations,ediscovery-process; legal-ops; bloglighthouse

What the administration’s early actions can spell for dynamic changes in regulation and compliance.On day one of his administration, President Biden got off to a bold start by signing more than a dozen executive orders on subjects ranging from student loans to deportation — including a freeze on all regulatory actions in process under the prior administration.In the subsequent 99 days, more orders, executive appointments, nominations, and legislative activities have contributed to a notable thaw in the regulatory sphere as the administration strives to fulfill the policy-driven promises made during the campaign. A recent Corporate Compliance Insights article suggests that companies “should look to bolster their compliance infrastructure ahead of this imminent wave of regulation,” an activity that legal departments would surely applaud.Although the full impact of activities from the first 100 days may not play out for some time, the combination of COVID-19 fallout and the actions of the new administration — especially the appointments of some agency leaders — is already beginning to change business, legal, and compliance dynamics. Many companies are already facing increased litigation and fraud investigations as a result of the pandemic with the expectation that incidents will rise; the potential for increased regulatory actions from agencies energized by new leadership will only intensify the need for a corporate response.Energized regulatory agencies with a consumer protection focus A more robust regulatory environment is expected under the Biden administration, especially for financial and monetary systems, with a greater focus on consumer protection. With Gary Gensler heading up the SEC, there will likely be an emphasis implementing regulatory measures or approaches to broaden the retail investor focus. The Federal Reserve Board will resume examination activities for all banks after previously announcing a reduced focus on exam activity in light of the coronavirus response. And, with Janet Yellen at the helm of the Treasury, there will likely be stepped-up enforcement and investigatory activities on several fronts, including a shoring up of the Dodd-Frank act, which was relaxed under the prior administration, and implementation of the Corporate Transparency Act to expose and combat money-laundering, which Yellen has said is “one of her highest priorities.”Rohit Chopra, awaiting confirmation as head of the Consumer Financial Protection Bureau, is also expected to play a role in increasing regulatory actions, reversing the prior administration’s more lax oversight and enforcement policies. Already, analysts say, bank examinations, student lending, subprime auto loans, debt collection, mortgage services, and payday loans are expected to come under renewed scrutiny.The M&A landscape is in flux, impacted substantially by the pandemic but now gaining renewed momentum. Due to COVID-19 and its impact on the economy, the DOJ and FTC have been on alert for antitrust violations. According to at least one major law firm’s assessment, there is likely to be increased antitrust enforcement by the DOJ in several key industries over the next several years including tech, health care, and agriculture as well as increased merger enforcement that will lead to more second requests and potential for litigation.Also affecting M&A activity is a possible increase in the capital gains tax that could spur even more activity ahead of its passage. The pending confirmation of Lina Kahn as a commissioner of the FTC marks the probability of greater investigative efforts to potentially break up the expanding reach of Big Tech. Google, Facebook, Microsoft, and Apple will be the most likely targets, but expanded investigations related to M&A in other industries are also probable. The healthcare and pharmaceutical industries, whose activities stand out in high relief due to the pandemic, are sure to face more scrutiny in terms of both monopoly pricing issues and market concentration, which Biden says he will aggressively tackle.The 100-day message? Be proactive and be prepared. One thing seems certain: the regulatory landscape will continue to be dynamic. The first 100 days is, after all, just the beginning. Increasing litigation and investigations, second requests, and the due diligence and regulatory reporting necessitated by just the few probable changes suggested above threaten to impact the workload of most corporate legal and compliance departments, which may already be overburdened and understaffed.The possibility of such activity is best met with well-prepared legal and compliance functions and a laser focus on corporate data, with the appropriate tools to manage it. Any proactive steps taken to ensure that the appropriate workflows are in place should stand companies in good stead, accelerating any necessary response and mitigating the costly effects of poorly handled document productions. Companies with teams at the ready to meet these data-heavy challenges will be in a much better position to respond quickly and efficiently should the need arise.antitrustblog, regulation, biden-administration, antitrustblog; regulation; biden-administrationlighthouse