In the March 19, 2026 edition of The Legal Intelligencer, Kelly Lavelle writes, “AI Systems and the Question of Confidentiality.”Much of the attention surrounding generative AI in litigation has focused on hallucinated authorities and AI-generated filings. But a different litigation risk arises when lawyers, or even clients themselves, enter client information into an AI platform. Before privilege or production issues arise, the more basic inquiry is whether the information was ever confidential in the first place. This question is particularly significant in e-discovery, where electronically stored information generated by AI systems may later become discoverable.

The U.S. District Court for the Southern District of New York’s decision in United States v. Heppner brings that issue into focus. Although the case has been described as a privilege ruling, the court’s analysis turned on a more basic issue: whether the information was confidential when it was entered into the AI platform. If client information is submitted to a system under terms that allow the provider to access, retain, or disclose it, the protections that depend on confidentiality, including attorney-client privilege and work product, may never attach.

In Heppner, a corporate executive under criminal investigation used the publicly available generative AI platform “Claude” to generate written analyses of potential defenses after receiving a grand jury subpoena. He later shared those documents with counsel. Following his arrest, FBI agents executed a search warrant at Bradley Heppner’s home and seized numerous documents and electronic devices. Heppner’s counsel later informed the government that among the seized materials were approximately thirty-one documents memorializing Heppner’s communications with the AI platform.

Through his counsel, Heppner asserted privilege over these documents, arguing that the information entered into the AI platform was learned, that he created the documents to facilitate discussions with counsel and obtain legal advice, and that he subsequently shared the AI outputs with his attorneys. His counsel acknowledged, however, that they did not direct Heppner to conduct the AI searches. The court rejected those claims. It held that the documents were not communications with an attorney, were not prepared by or at the direction of counsel, and, critically, were not confidential in light of the platform’s privacy policy.

The court’s analysis centered on the conditions under which the information was entered into the system. The provider’s terms stated that user inputs and outputs were collected and retained and that the company reserved the right to disclose data to third parties, including governmental authorities. Under those conditions, the court concluded that Heppner lacked a reasonable expectation of confidentiality at the moment of disclosure.

The court also rejected Heppner’s contention that he communicated with Claude for the “express purpose of talking to counsel.” In doing so, the court looked to the platform’s own representations. Claude expressly disclaimed providing legal advice. When asked whether it could provide such advice, the system responded that it was not a lawyer, could not offer formal legal recommendations, and advised users to consult a qualified attorney.

The court acknowledged that the implications of artificial intelligence for the law are only beginning to be explored. The court emphasized that AI’s novelty does not place it outside established legal principles, including those governing attorney-client privilege and the work-product doctrine. AI does not change the basic rules.

The opinion highlights a familiar but often underemphasized principle that privilege attaches only when communications are intended to be confidential and were, in fact, kept confidential. In the AI context, if a platform’s terms allow provider use beyond delivering the requested service, such as model training, analytics, affiliate sharing, or extended retention, the user may be acting inconsistently with the intent to preserve confidentiality at the moment of disclosure. The issue is not a subsequent waiver. It is that the platform itself may defeat confidentiality at inception.

This reasoning extends beyond generative AI. Courts have consistently held that employees may waive attorney-client privilege when using employer email systems to communicate with counsel, with the analysis turning on whether the employee had an objectively reasonable expectation of confidentiality. In those cases, the inquiry focuses on whether the intent to communicate in confidence was objectively reasonable under the circumstances. Heppner suggests that AI platforms may be subject to similar scrutiny. The terms governing data retention and disclosure may determine whether any protection exists at all.

The court also reaffirmed that privilege remains grounded in professional accountability. Recognized privileges depend on a relationship with a licensed professional who owes fiduciary duties and is subject to discipline. Generative AI does not occupy that role. Even if an output resembles legal advice, it is not a communication with counsel.

However, the court suggested that if counsel had directed the use of the AI tool within a structured framework, the analysis might have been different. That distinction highlights the importance of control. When AI use is integrated into a counsel-directed process under defined terms, protection arguments may be stronger. When it is independent and unsupervised, confidentiality may fail at the start.

Platform terms of service are therefore central. Many providers claim licenses to user inputs and outputs broader than a confidentiality-preserving relationship would tolerate, sometimes including rights to use content for service improvement, analytics or model training. However, this concern does not apply in the same way to all AI tools. Paid legal research platforms or firm-licensed systems are often governed by professional services agreements that include confidentiality obligations and defined data controls. In those contexts, the vendor functions more like a traditional litigation support provider than a public AI service. Even there, however, the analysis may turn on the contract. Courts will look at the terms to determine what they permit and how the provider handles user content.

These issues directly affect attorney-client privilege. Privilege protects confidential communications made for the purpose of obtaining or providing legal advice. The problem is not simply waiver. It is that the basic requirements for privilege may never have been satisfied. The work-product doctrine raises a similar issue. Work product protects materials prepared in anticipation of litigation. If those materials are created on a public nonconfidential platform, it weakens the argument that they reflect protected legal strategy shielded from disclosure.

Heppner reinforces the basic rule that privilege depends on confidentiality at the time the communication is made. It does not arise simply because a document is later shared with counsel. In the AI context, that means platform terms, data handling practices, and professional controls must align with confidentiality requirements before client information is entered. The focus should be less on whether AI interactions are discoverable and more on whether confidentiality ever attached. As Heppner shows, confidentiality is not assumed simply because a document resembles legal analysis. It depends on the conditions under which the information was created and maintained.

Kelly A. Lavelle is Senior Counsel at Kang Haggerty. She focuses on e-discovery and information management, from preservation and collection to review and production of large volumes of electronically stored information. Contact her at klavelle@kanghaggerty.com.

Reprinted with permission from the March 19, 2026 edition of “The Legal Intelligencer” © 2026 ALM Global, LLC. All rights reserved. Further duplication without permission is prohibited. Request academic re-use from www.copyright.com. All other uses, submit a request to asset-and-logo-licensing@alm.com. For more information visit Asset & Logo Licensing.

In the November 20, 2025 edition of The Legal Intelligencer, Kelly Lavelle writes, “Understanding and Applying Local Rules When Drafting ESI Protocols.“

ESI protocols govern how parties preserve, collect, review, and produce electronic evidence in federal litigation. What once was an obscure procedural topic now lies at the center of nearly every civil case involving documents, emails, databases and other forms of electronic data. ESI protocols provide structure and predictability in an area that can otherwise be costly and difficult to manage. A well-drafted ESI protocol defines production formats, metadata requirements, search terms, and privilege review procedures, reducing disputes and helping discovery move forward efficiently.

The Role of Local Rules in Electronic Discovery

With ESI protocols now a regular part of litigation, local rules and court practices play a more significant role in guiding the process. While the Federal Rules of Civil Procedure provide the foundation for electronic discovery, many district courts have developed their own local rules and forms to guide parties in drafting ESI protocols. Some districts have detailed local rules governing electronic discovery, while others, including the Eastern District of Pennsylvania, have not enacted a formal local rule governing ESI, but rely instead on individual judges’ policies and preferences that serve the same purpose. These guidelines show that courts expect parties to manage ESI in an organized way and to address potential issues in advance rather than waiting for them to arise. Following local practice helps lawyers know what the court expects, makes negotiations smoother, and saves time by avoiding mistakes the court has already ruled out.

Recent case law demonstrates how these local practices guide judicial decisions on ESI. In Hall v. Warren, 2025 WL 1392294 (W.D.N.Y. May 14, 2025), the parties failed to reach an agreement on an ESI protocol governing the production of electronically stored information. When negotiations fell apart, plaintiffs moved to compel production of metadata from internal reports and investigative files, arguing that such information was necessary to verify whether documents had been altered and to confirm their authenticity and completeness. Unable to obtain agreement from the parties, the court issued its own ESI protocol order that included selected provisions from each side’s proposal.

The defendants filed multiple objections to the court’s order, arguing that the order violated the district court’s local rules and imposed undue cost and technical burden. They claimed the order mandated universal metadata production, required technical tasks they could not perform, demanded compatibility with opposing counsel’s document review platform, and ordered native production without proper justification.

The court rejected these arguments, clarifying that the ESI order did not require many of the things defendants claimed it required and that the order’s actual requirements were consistent with the local rules and, in many instances, mirrored the local rules specific provisions. The order also provided flexibility for the parties to meet and confer on alternate formats or cost-sharing if a production became disproportionately burdensome.

The critical lesson from Hall is that the defendants misunderstood both the ESI order and the local rules they said it violated. The defendants clearly had read the district’s local rules because they cited them throughout their objections. Their problem was not ignorance of the local rules but misunderstanding what those rules actually required. The defendants thought the ESI order required things it did not require. They believed it violated local rules when it actually followed them. They argued that certain procedures were mandatory when the order actually provided flexibility. Because they misunderstood the local rules from the beginning, they could not negotiate effectively. As such, the defendants ended up with a court-imposed protocol that likely was less favorable than what they could have achieved through informed negotiation.

While Hall shows how local rules guide substantive resolution of ESI disputes, the case Husidic v. FR8 Solutions, No. 3:24-cv-963-WGY-SJH (M.D. Fla. Sept. 10, 2025), demonstrates the importance of complying with local procedural requirements even when parties agree. In Husidic, the parties submitted a joint motion requesting that the court enter the parties’ stipulated ESI protocol as an order. The magistrate judge denied the motion identifying three defects. First, the motion cited no legal authority for the proposition that courts should routinely enter agreed ESI protocols as orders. Second, the parties failed to include the memorandum of law required by the U.S. District Court for the Middle District of Florida’s local rules governing motion practice. Third, the request lacked any showing that court adoption of the protocol was necessary or appropriate.

The magistrate judge also identified a substantive issue with the parties’ proposed stipulation, which included ambiguous provisions referencing privilege and work-product protections that might implicate Federal Rule of Evidence 502, yet neither the stipulation nor the motion addressed Rule 502(d). The court emphasized that if parties seek a non-waiver order, they must make the request expressly and provide factual support demonstrating why such an order is necessary.

In declining to endorse the parties’ ESI protocol, the court implied that judicial resources should not be spent approving private agreements that can be managed through cooperation and adherence to the local rules. Further, compliance with local procedural requirements is essential, even when parties agree on the substance of an ESI protocol. Counsel must understand not only the local rules governing electronic discovery but also the local rules governing motion practice and the standards for obtaining court orders.

Practical Guidance for Counsel

For lawyers, these cases show that the most effective ESI protocol is one based on the local rules of the district court or specific judges’ policies and procedures. Counsel should familiarize themselves not only with the federal rules but also with the district court’s ESI checklists, policies, procedures, and discovery guidelines, many of which provide practical direction that supplements the federal rules. Before the Rule 26(f) conference, counsel should review the district’s local rules on electronic discovery and consider how those rules, and the judge’s preferences are likely to influence court resolution of any disputes. By following local rules from the beginning, parties can reduce the likelihood of motion practice and avoid judicially imposed resolutions that may be less favorable than a negotiated agreement.

Kelly A. Lavelle is an associate at Kang Haggerty. She focuses on e-discovery and information management, from preservation and collection to review and production of large volumes of electronically stored information. Contact her at klavelle@kanghaggerty.com.

Reprinted with permission from the November 20, 2025 edition of “The Legal Intelligencer” © 2025 ALM Global, LLC. All rights reserved. Further duplication without permission is prohibited. Request academic re-use from www.copyright.com. All other uses, submit a request to asset-and-logo-licensing@alm.com. For more information visit Asset & Logo Licensing.

OpenAI CEO Sam Altman recently warned that ChatGPT conversations are not legally protected and can be used as evidence in court. Speaking on a podcast, Altman acknowledged that OpenAI is legally required to retain user chats, including deleted ones, due to a current court order discussed later in this article. Comparing AI conversations to those with doctors, lawyers, or therapists, Altman argued that similar confidentiality protections should exist but currently do not, leaving sensitive exchanges with public AI tools fully exposed to discovery, an issue he described as needing to be addressed with urgency.

The use of AI tools like ChatGPT and Claude has created new issues for the discovery process. Lawyers must recognize that AI queries and outputs may qualify as electronically stored information (ESI) under both federal and state discovery rules. As AI technology becomes more integrated into legal practices, discovery requests are beginning to target the use of these technologies, seeking access to AI-generated documents, search histories and communication logs.

Many users may view AI tools as private assistants rather than potential witnesses. However, the use of AI tools like ChatGPT and Claude can inadvertently expose sensitive information, including legal strategies and privileged facts. Users may not realize that third-party AI platforms can be compelled to produce records during litigation, potentially compromising confidentiality and privilege. Many platforms keep detailed logs that include prompts and generated output, often tied to user accounts. Users may be surprised to learn that if they have employed these tools to draft documents or summarize confidential facts, those entries may be discoverable. This misunderstanding can create serious risks.

Several recent cases illustrate the discovery concerns associated with AI use. In some instances, AI-related ESI has been sought in discovery, challenging both privilege and work product protections. These cases highlight the importance of understanding the discovery implications of AI use and the need for protective measures. The discoverability of ChatGPT searches and their status as non-privileged information in legal proceedings may depend on the context in which the searches are conducted and the applicable privileges.

In some cases, courts have found that AI prompts and outputs, particularly when drafted by counsel, can constitute attorney work product. In Tremblay v. OpenAI, No. 23-cv-03223-AMO, 2024 WL 3748003, at *2-3 (N.D. Cal. Aug. 8, 2024), the court held that prompts created by attorneys reflected their mental impressions and opinions, making them work product rather than mere factual material. Applying that same reasoning, a California district court recently concluded that certain prompts, settings, and outputs from the Claude AI model were likewise protected, rejecting the argument that such materials were automatically discoverable. See Concord Music Group v. Anthropic PBC, 2025 WL 1482734, at *1 (N.D. Cal. May 23, 2025). The court emphasized that these materials were generated during counsel’s investigative process and therefore qualified for work product protection. However, the court also recognized that work product protection can be waived when a party relies on such materials in pleadings or motions. Here, the plaintiffs used specific prompts and outputs in their complaint and preliminary injunction filings, producing nearly five thousand prompt-output records that they relied upon. Under the “fairness principle,” this created a limited waiver. However, the court refused to extend it to all prompts, settings, and outputs, finding that discovery requests for every AI interaction were overreaching and not “closely tailored” to the opposing party’s legitimate needs nor limited to what is necessary under the fairness principle.

On the other hand, and perhaps the most sweeping example is the ongoing New York Times v. OpenAI lawsuit, which alleges that OpenAI unlawfully used millions of Times articles to train its AI models, including ChatGPT. In connection with that case, on May 13, 2025, Magistrate Judge Ona T. Wang ordered OpenAI to “preserve and segregate all output log data that would otherwise be deleted on a going forward basis,” a directive affecting hundreds of millions of ChatGPT users. See In re OpenAI Copyright Infringement Litigation (relating to The New York Times v. Microsoft, 23-cv-11195), No. 25-md-3143 (SHS) (OTW), ECF No. 551, at 2 (S.D.N.Y. May 13, 2025). OpenAI objected, arguing the order forced it to “disregard legal, contractual, regulatory, and ethical commitments” and retain up to 60 billion conversations, of which the plaintiffs estimated only 0.006% might be relevant. See OpenAI Defs.’ Supplemental Opp’n to News Pls.’ Mot. Regarding Output Logs , No. 25-md-3143 (SHS) (OTW) (S.D.N.Y. May 23, 2025), ECF No. 578. The district judge rejected those arguments, affirming the order and noting that OpenAI’s own terms of use allowed preservation for legal requirements. See Order, No. 25-md-3143 (SHS) (OTW), ECF No. 712 (S.D.N.Y. June 26, 2025). Although the court later clarified that certain categories were excluded, the case highlights how deleted AI data can become subject to preservation and discovery.

Lawyers should address these concerns and advise clients at the outset that interactions with AI tools may be discoverable and should be treated accordingly. This means instructing clients not to input privileged or confidential strategy into public or unsecured AI platforms. Clients should understand that the same caution they would apply to an email applies to AI prompts.

Further, the integration of AI tools like ChatGPT into legal practices necessitates a careful consideration of discovery obligations. Firms should adopt clear policies governing the use of AI tools for litigation tasks. These policies should address acceptable uses, data protection measures, and procedures for handling AI-generated content.

Kelly A. Lavelle is an associate at Kang Haggerty. She focuses on e-discovery and information management, from preservation and collection to review and production of large volumes of electronically stored information. Contact her at klavelle@kanghaggerty.com.

Reprinted with permission from the August 21, 2025 edition of “The Legal Intelligencer” © 2025 ALM Global, LLC. All rights reserved. Further duplication without permission is prohibited. Request academic re-use from www.copyright.com. All other uses, submit a request to asset-and-logo-licensing@alm.com. For more information visit Asset & Logo Licensing.

In the January 30, 2025 edition of The Legal Intelligencer, Kelly Lavelle writes, “The Importance of Federal Rule of Evidence 502 and Its Impact on Privilege.“

Federal Rule of Evidence 502 governs the treatment of inadvertent disclosures of privileged attorney-client communications or work-product materials. While Rule 502 is an evidence rule, the cases interpreting and applying it focus on its impact on the scope of discovery. Enacted by Congress in 2008, it was designed to address the growing risks of inadvertent disclosure in the era of e-discovery. The rule acknowledges the practical challenges of privilege review and aims to reduce the associated costs and uncertainties. The comments to Rule 502 highlight the value of confidentiality orders in limiting costs of privilege review, especially in cases involving e-discovery.

Subsection (a) of the rule addresses intentional disclosures, while subsection (b) governs inadvertent disclosures. Specifically, Rule 502(b) establishes the default framework for determining whether an inadvertent disclosure results in a waiver of privilege. Under this rule, privilege is preserved if three conditions are met: the disclosure was inadvertent; the producing party took “reasonable steps” to prevent the disclosure; and upon discovery of the disclosure, the producing party promptly took reasonable steps to rectify the error, including compliance with Federal Rule of Civil Procedure 26(b)(5)(B).

Importantly, Rule 502(b) does not require a responding party to conduct a post-production privilege review to determine whether any protected communication or information was inadvertently disclosed. However, the rule does direct a responding party to address any “obvious indications” that a protected communication or information may have been inadvertently produced. The challenge arises from the fact that courts often apply the reasonableness standard differently, depending on the interpretation of what constitutes “reasonable steps.” Because of the inconsistency, parties can never be completely certain that any given privilege review procedure will be reasonable.

Rule 502(d) provides certainty. It offers a more predictable alternative to the default framework by allowing courts to issue orders that preclude privilege waivers, regardless of the care taken during document review. Specifically, Rule 502(d) provides that a federal court may order that the privilege or protection is not waived by disclosure related to the pending litigation, and that disclosure is also not a waiver in any other federal or state proceeding. This broad application ensures a consistent approach to preserving privilege of the communication or information.

There are several additional key benefits that come with Rule 502(d). In addition to preventing waiver, parties can incorporate into the order a detailed agreement specifying its scope and effect on the litigation, offering a more tailored and comprehensive understanding of the order’s implications. The order also imposes a strict obligation requiring that privileged documents are returned to the disclosing party regardless of the care taken by the producing party prior to production. Furthermore, the court has the authority to issue a Rule 502(d) order sua sponte, without necessitating explicit agreement from the parties involved.

One area that remains unclear is the effect of a 502(d) order on intentional disclosures. A key case on this issue is Lubrizol v. IBM, 2024 WL 941686 (N.D. Ohio Feb. 8, 2024). In this case, Lubrizol accused IBM of fraud and various torts in the development of an enterprise resource planning software project. Lubrizol later amended its complaint to include allegations of spoliation by IBM, specifically regarding the deletion of electronically stored information from both current and former IBM employees who were integral to the project. IBM sought a court order under Rule 502(d), seeking to disclose certain documents without waiving attorney-client privilege or work product protection. Lubrizol argued that the court lacked authority to enter a Rule 502(d) order that would permit IBM to intentionally (rather than inadvertently) disclose privileged information without constituting a subject matter waiver of all other documents and communications on the same topic.

While the Sedona Conference suggests that a Rule 502(d) order may apply not only to inadvertent waiver but also to intentional disclosure, the court in Lubrizol determined that there was ambiguity surrounding this issue. The court was primarily concerned with the possibility that IBM’s proposed 502(d) order would allow it to disclose documents that support its position while continuing to withhold other less favorable documents. It ultimately held that it lacked the authority to grant such an order for intentional disclosures. The court relied on case law from other jurisdictions that found that Rule 502(d) does not authorize strategic or selective disclosure of some privileged materials for use in litigation while withholding others on the same subject.

Reprinted with permission from the January 30, 2025 edition of “The Legal Intelligencer” © 2025 ALM Media Properties, LLC. All rights reserved. Further duplication without permission is prohibited, contact 877-257-3382 or reprints@alm.com.

In the August 8, 2024 Edition of The Legal Intelligencer, Kelly Lavelle writes, “Impact of Blockchain on Data Preservation and Discovery.”

Expanding Beyond Cryptocurrencies

Originally developed as the foundation for cryptocurrencies like bitcoin, blockchain technology’s potential extends far beyond digital currencies. Its decentralized and secure nature makes it a transformative tool for data preservation and management across various fields, including health care, supply chain management, asset administration, banking, and financial markets.

Traditionally, e-discovery has relied on centralized systems and methods for gathering data. These systems often face challenges related to data security and integrity. Blockchain technology, however, will transform this landscape significantly. Unlike centralized systems, blockchain offers a decentralized ledger that records all transactions from its beginning in a secure and transparent manner. This ledger serves as an indisputable chain of custody, providing enhanced protection against data spoliation and ensuring that all changes are permanently recorded and traceable.

As businesses across various industries increasingly adopt blockchain, it will become a critical source of discoverable electronically stored information (ESI). The potential benefits of blockchain for e-discovery and data preservation are substantial, making it an area of growing interest and importance.

Blockchain networks operate on an immutable ledger composed of individual blocks. Each block is comprised of a header containing a date, time stamp, and other metadata, followed by a chronological list of transactions. Simply put, each block contains three main components:

• Data—The data varies depending on the type of blockchain. For example, in Bitcoin, the data includes information about the sender and receiver, as well as the amount of Bitcoin transferred.
• Hash—The hash is a unique identifier representing the block’s contents, similar to a fingerprint. It is crucial for detecting any changes within the block.
• Hash of the Previous Block—This links each block to the preceding one (forming a chain), ensuring the blockchain’s chronological order and integrity. Once data is recorded, it cannot be altered or deleted without changing the hash, thereby making all of the following blocks invalid.

Blockchain is a decentralized system, which fundamentally differs from centralized systems that have a single point of failure. In centralized systems, data is stored in a single computer or system, making the entire system vulnerable if attacked or compromised. Hackers often exploit the centralization model. In contrast, a decentralized helps mitigate the risk of data loss. However, challenges such as blockchain forking and chain reorganization can affect the immutability of the data, raising concerns about data integrity. Nonetheless, blockchain technology is set to revolutionize e-discovery by introducing new methods of data preservation and transparency.

E-Discovery Legal Landscape

Several jurisdictions have started accepting blockchain records in litigation, recognizing that courts are increasingly likely to admit such evidence under conditions similar to other forms of electronic data. As this technology evolves, several considerations arise, particularly regarding the discoverability of blockchain data. Under Rule 34 of the Federal Rules of Civil Procedure, a party can request access to another party’s data compilations within the scope of discovery. Blocks can be considered “data compilations.”

The process for discovery of a block or blockchain is the same as for other electronically stored data: identification, preservation, collection, examination, and analysis. While blockchain data is fundamentally electronically stored information, its unique security features and public accessibility—allowing users to write and view data without altering previously recorded information—distinguish it from other forms of ESI. Despite these advantages, challenges may arise regarding the discoverability and admissibility of blockchain records in court.

One such challenge that the application of blockchain data may face is related to authentication. The Federal Rules of Evidence address the authentication of ESI in Rule 902. In the last few years, Rule 902 was expanded to include Sections 902(13) and 902(14), which address the self-certification of electronic data. These amendments provide a strong foundation for admitting blockchain evidence by simplifying the process of authenticating ESI, allowing for the self-certification of certain digital evidence, and reducing reliance on expert testimony.

However, the unique aspects of blockchain technology, such as the structure and lack of a single custodian, introduce additional challenges to the authentication process.

Emerging Caselaw

The recent high-profile case against FTX and Sam Bankman-Fried highlighted the critical role that blockchain can play in legal evidence. FTX Exchange, once the third-largest crypto exchange, encountered significant trouble when a hidden vulnerability within its code was discovered in late 2022. The collapse of the exchange and subsequent legal proceedings have demonstrated how blockchain can be used to trace the flow of funds and verify the authenticity of transactions. This transparency helps establish a clear chain of custody for digital assets, making it easier to prove or disprove claims of fraud.

Courts have also been increasingly adapting the Federal Rules of Civil Procedure to accommodate technological advancements in conducting modern discovery. For instance, in a recent money laundering case involving Bitcoin, the U.S. District Court for the District of Columbia allowed expert testimony on blockchain analysis software. This decision acknowledges the growing reliance and reliability of blockchain technology in legal proceedings.

Similarly, in a case in the District of New Jersey, the court permitted expedited discovery, allowing the plaintiff to issue subpoenas to cryptocurrency exchanges for all documents related to the wallet addresses of potential hackers. This included account opening and closing documents and the identity of the account holders. The court, applying a good cause standard, ruled the information discoverable under the broad scope of Rule 26, demonstrating the courts’ increasing willingness to allow access to blockchain technology in the discovery process.

Embracing Potential Challenges

As blockchain becomes a more prominent source of evidence, legal professionals must prepare for the unique challenges it presents in collection and review. While courts are beginning to address issues related to this new form of electronic data, many challenges are still emerging. Issues such as privilege, data privacy, the proportionality of data collection, and blockchain data management across different jurisdictions will need to be carefully navigated. Despite these challenges, the potential benefits of blockchain for e-discovery and data preservation are substantial.

Kelly A. Lavelle is an associate at Kang Haggerty. She focuses on e-discovery and information management, from preservation and collection to review and production of large volumes of electronically stored information. Contact her at klavelle@kanghaggerty.com.

Reprinted with permission from the August 8, 2024 edition of “The Legal Intelligencer” © 2024 ALM Media Properties, LLC. All rights reserved. Further duplication without permission is prohibited, contact 877-257-3382 or reprints@alm.com.

In the June 10, 2024 edition of The Legal Intelligencer, Kelly Lavelle wrote, “Navigating the Shift: Understanding Modern Attachments in E-Discovery.”

The development of new file-sharing techniques creates a dynamic challenge for legal professionals and raises significant questions about electronic discovery. Most organizations now utilize cloud-based file systems for file creation, organization, and sharing. Rather than cluttering emails with attached documents, links to files stored in web-based clouds are sent, directing recipients straight to the source document. These hyperlinks, often called “modern attachments” or electronic “pointers,” mark a shift in document-sharing practices. This shift has led to a decline in the use of traditional email attachments. While the impact on e-discovery is still evolving, it is one of the key areas to watch this year. Despite the growing prevalence of the use of hyperlinks, only a handful of courts have addressed the issue of modern attachments to date.

Traditionally, email attachments have been regarded as part of an email’s “family” during discovery. However, with the emergence of modern attachments, these files are not part of the underlying message file—therefore, the traditional notion of a “family” is absent. Whether courts will treat these modern attachments as attachments in the traditional sense remains to be seen. Notably, the Sedona Conference defines a “document family” as “a collection of pages or files produced manually or by a software application, constituting a logical single communication of information, but consisting of more than a single stand-alone record.” This definition suggests that a hyperlinked file shared in an email could be considered part of a “document family.” These family associations are important to understanding the context of the documents. Emails without their attachments often lack significance. The documents exchanged within emails are often more important evidence. As with all ESI, the discoverability of the link’s target focuses on whether the (nonprivileged) target is responsive and within the care, custody, or control of the producing party. If the link is part of a relevant, responsive, non-privileged communication, it must be produced. However, courts have begun to distinguish between traditional and modern attachments for discovery purposes.

The court highlighted the distinction between traditional and modern attachments in the 2021 case, Nichols v. Noom, 2021 WL 948646 (S.D.N.Y. March 22, 2021). In Noom, the parties began to negotiate an ESI protocol, but disagreements led to multiple court conferences. Ultimately, Noom agreed to collect relevant data from various sources, including Gmail, G-chat, and Google Drive, and to produce extensive metadata. The parties agreed to the use of Google Vault to collect documents from Google Drive despite the absence of the “filepath” metadata. However, the parties disagreed with the use of Google Vault to collect Gmail emails. Plaintiffs filed a motion to require Noom to use a forensic evidence collector to collect Gmail documents to ensure any hyperlinked documents were also pulled as part of the document “family.” The court permitted Noom to use Google Vault, emphasizing that a producing party can choose its reasonable search and collection methods. To address concerns about the hyperlinked documents, the court allowed plaintiffs to raise issues about missing hyperlinks, and Noom agreed to provide the documents for a reasonable number of cases. Plaintiffs filed a motion for reconsideration. The court denied the motion, noting that the ESI order did not treat hyperlinks as attachments, nor did the order define “attachments.” The court concluded that hyperlinks are not equivalent to attachments and stood by the initial ruling that the defendant did not need to re-collect data with familial attachments in place, explaining that while attachments are a necessary part of a communication, hyperlinked documents may not be.

In another recent case, In re Insulin Pricing Litigation, No. 3:17-cv-0699 (BRM) (RLS), MDL No. 2080 (D.N.J. May 28, 2024), the U.S. District Court of New Jersey addressed several contested ESI issues in connection with the parties’ proposed ESI protocols. The court held that hyperlinks are not the same as traditional attachments, emphasizing that courts must determine whether commercially available tools can maintain family relationships in the context of hyperlinks and if the use of such tools is proportional to the needs of the case and not unduly burdensome.

Regardless of the current rulings on the issue, it is evident that addressing the treatment of hyperlinks in discovery requires proactive measures within the ESI protocol. Federal Rule of Civil Procedure 34 permits a party to specify the form or forms of production; therefore, the requesting party should carefully consider the hyperlink issue when crafting requests. The ESI agreement should include language clarifying how hyperlink documents should be handled. If the source documents cannot be produced with their parent email, at the very least, the file path metadata should be produced so that the documents can be matched with the parent email.

In the January 26, 2024 edition of The Legal Intelligencer, Kelly Lavelle wrote, “Strategies for Successful Recovery of E-Discovery Expenses.”

E-discovery has evolved into an integral component of the litigation process. With vast amounts of electronic data available, expenses associated with e-discovery can be substantial. In federal courts, the presumption is that the responding party is responsible for bearing the costs associated with discovery requests, including those related to electronic discovery. However, there are avenues through which parties can seek recovery of e-discovery expenses. Parties should understand the basis upon which courts will allow recovery of these costs and establish reasonable limits on the scope of discovery at the beginning of the litigation process. This proactive approach will allow litigants to manage and control the financial aspects of e-discovery more effectively.

The general rule is that a party producing documents pays the cost of production. However, an exception to this rule exists. Federal Rule of Civil Procedure Rule 26(c) provides parties with the possibility of cost-shifting during the course of litigation. In 2015, Rule 26 was amended to include a key change to 26(c)(1)(B). The amendment expressly confirmed the authority of federal courts to shift costs to protect parties from undue burden or expense. The advisory committee note accompanying the amendment clarified that the purpose of the change was “‘to include an express recognition of protective orders that allocate expenses for disclosure or discovery’ to ‘forestall the temptation that some parties may feel to contest’ a court’s authority to issue such orders.” It is important to note, however, that the advisory committee also cautioned against making cost-shifting a routine practice, emphasizing the need for restraint in its application.

A party seeking to shift costs under Rule 26 may do so by filing a motion with the court. The burden is on the responding party to demonstrate that the costs should be shifted. If the expenses associated with e-discovery are deemed an unreasonable burden on the producing party, a court may consider shifting some or all of the expenses to the requesting party.

Many courts have interpreted the language of Section 1920(4) as it applies to e-discovery expenses. Some courts have taken an expansive view of “making copies” and have awarded costs for TIFF conversion and project management; collecting, searching, and processing ESI; and costs related to applying date ranges, custodian filters, and deduplication. Conversely, other courts have adopted a narrower interpretation, disallowing many of the same costs. Consequently, a party seeking cost-shifting under Section 1920 must ensure that the costs align with the statutory limits. Parties often rely on invoices from e-discovery vendors to prove the expenses should be covered. However, the bills can be vague and confusing, which could lead a court either to deny cost-shifting altogether for failure to meet the statutory requirements or to create its own estimate of the costs. It is imperative for parties to meticulously review vendor invoices, ensuring a detailed breakdown of charges, as undocumented costs are unlikely to be awarded by the court.

To navigate current trends and strategies for successful cost-shifting, proactive e-discovery planning becomes crucial. Parties should engage in open discussions about the scope and cost of ESI productions, conducting a thorough early case assessment to determine e-discovery scope and estimate potential costs. Utilizing predictive advanced data analytics can further assist in evaluating the cost and relevance of ESI requests. Cooperative and good-faith negotiations between parties can streamline the e-discovery process and reduce costs. If one party unreasonably resists negotiations, there is an increased chance that a court will shift costs. When presenting the case to the court, clearly articulating reasons such as proportionality, good-faith cooperation, and the potential burden on the client will increase the chances that cost-shifting requests will be granted.

Effectively recovering e-discovery expenses through cost-shifting demands a strategic and proactive approach. Parties can significantly enhance their chances of shifting the financial burden associated with e-discovery by understanding the legal principles involved, engaging in open communication, and presenting a compelling case to the court. In cases with substantial e-discovery expenses, counsel should consider seeking advance relief under Rule 26 to either limit, share or shift vendor costs. The standards set by Rule 26 for such relief offer the court broader options than the potentially narrow interpretation of the “making copies” standard applicable to taxable costs recoverable post-judgment.

Furthermore, a comprehensive understanding of a jurisdiction’s laws governing the recovery of e-discovery expenses is crucial and should be assessed at the early stages of a case. This knowledge serves as a guide for proceeding with discovery and offers insights into potential exposure. Given the continuous evolution of technology, the significance of cost-effective e-discovery strategies, including mechanisms like cost-shifting, remains paramount. Legal professionals can effectively navigate the complexities of e-discovery and mitigate financial challenges by establishing clear guidelines, maintaining meticulous documentation, exploring innovative cost-shifting strategies, embracing technology and staying abreast of pertinent legal developments.

In the October 26, 2023 edition of The Legal Intelligencer, Kelly Lavelle wrote, “Technology-Assisted Review: A Superior Approach in Legal Document Review.”

Technology-assisted review (TAR) has changed how lawyers manage and analyze vast volumes of electronic data in the ever-changing landscape of legal document review. Traditionally, search terms have been the preferred method in the e-discovery process. However, TAR is rapidly emerging as a superior alternative, offering numerous benefits over conventional search terms in legal document review.

Technology-assisted review (TAR) is a process of having computer software electronically classify documents based on input from reviewers to expedite the organization and prioritization of the document collection. As reviewers train the software, it learns to identify and highlight relevant information and ensure quality control accurately. TAR allows reviewers to make decisions rapidly by prioritizing the most critical documents. TAR has been accepted by the U.S. courts since the seminal 2012 decision in Da Silva Moore v. Publicis Groupe & M.S.L. Group, 287 F.R.D. 182 (S.D.N.Y. 2012) and is now viewed as black-letter law.

The landscape of technology-assisted review options includes: TAR 1.0, also known as “predictive coding” or “simple active learning,” TAR 2.0, known as “continuous active learning,” TAR 3.0, which is similar to continuous active learning but applied to cluster centers and TAR 4.0 known as hybrid multimodal I.S.T. (intelligently spaced training) predictive coding.

There are several differences between TAR 1.0 and TAR 2.0, which lie in how the algorithm is trained. TAR 1.0 software training begins by taking a random sample of documents from the entire TAR set. A reviewer then codes those documents, and based on the coding in that set (seed set), the software generates a predictive model that is applied across all relevant documents. In contrast, with TAR 2.0—the more advanced approach, the reviewer and software training occur simultaneously, and the algorithms are continuously learning as the documents are reviewed. TAR 3.0 combines the advantages of TAR 1.0 and TAR 2.0. The key aim of TAR 3.0 is to leverage the features of TAR 2.0 with new techniques that will allow for earlier and smarter identification of relevant documents. TAR 4.0 uses a combination of human and machine functions to efficiently and accurately identify relevant data. TAR 3.0 and 4.0 essentially fall under the TAR 2.0 umbrella.

Legal professionals have shifted toward adopting TAR 2.0 due to various advantages. In particular, continuous active learning has been shown to reach higher levels of recall, identifying a greater number of relevant documents more quickly and with less effort by the reviewer than TAR 1.0. Continuous active learning can also readily accommodate changes in the scope of discovery and rolling document productions since it continues training throughout the review process. A TAR 1.0 algorithm stops training when it reaches stable quality results, regardless of how many documents are subsequently reviewed, and requires manual re-training after each document review cycle is complete. A TAR 2.0 algorithm is trained by every coding decision until the review stops. Because the TAR 1.0 algorithm is fully trained before the review begins, it does not adapt to changes in the scope of discovery, such as the addition of documents in a rolling production or the addition of legal issues involved.

Determining which protocol best fits a particular matter depends on case objectives and requires a more detailed understanding of the various methodologies. Whichever variation is used, there are a number of key benefits to using TAR in document review.

Enhanced Precision and Recall

One of the primary advantages of TAR is its ability to enhance both precision and recall significantly. In the context of TAR, precision is a measure of how often an algorithm accurately predicts a document to be responsive. Essentially, it measures the percentage of documents produced that are actually responsive. Recall is a measure of completeness, referring to the percentage of relevant documents identified within the entire universe of documents.

Traditional search terms rely on specific keywords or phrases, potentially missing relevant documents that do not contain those exact terms. TAR, however, uses sophisticated machine-learning algorithms to identify document patterns. This advanced approach enables TAR to uncover relevant documents that might have been overlooked relying solely on search terms.

Reduced Volume of Irrelevant Documents

Search terms often generate large sets of irrelevant documents, burdening reviewers with time-consuming manual review. TAR minimizes this burden by prioritizing the review of documents most likely to be relevant. TAR learns from the coding decisions applied by the reviewers, prioritizes the most likely relevant documents, and excludes irrelevant ones. For projects where documents do not need to be reviewed before production, technology-assisted review can quickly separate the documents into relevant and irrelevant categories without review, allowing for quick production and substantial time and cost savings.

Improved Consistency and Defensibility

TAR offers a consistent and defensible approach to document review. From the initial approval of its use in Da Silva Moore, TAR has become a staple in modern litigation. Unlike search terms, which can be ambiguous and susceptible to implementation errors, TAR’s machine-learning algorithms apply consistent criteria across all documents. This uniformity not only enhances accuracy of the review process but also bolsters its defensibility in legal proceedings, as the process is well-documented and transparent.

Time and Cost Efficiency

Numerous courts have recognized the cost-saving benefits of technology-assisted review. By using TAR, legal professionals can significantly reduce review time, eliminating the hours spent on manual document review and reducing attorney fees substantially. Further, TAR provides the advantage of early case assessment by prioritizing relevant documents, thereby reducing the overall volume of documents. This proactive approach provides attorneys with the necessary information to make informed decisions about case strategy, settlement negotiations, or the need for additional evidence. Ultimately, TAR saves both time and valuable resources.

The advantages of technology-assisted review over traditional search terms in the modern legal landscape are clear and compelling. TAR not only offers enhanced precision but also drastically reduces the amount of irrelevant documents in the review set. TAR provides improved consistency coupled with significant cost savings. Its adaptability and early case assessment capabilities further solidify its role as a superior approach to document review in e-discovery. As technology continues to advance, legal professionals should embrace TAR as an invaluable tool in the search for efficient, accurate, and cost-effective legal document review.

Kelly A. Lavelle is an associate at Kang Haggerty. She focuses on e-discovery and information management, from preservation and collection to review and production of large volumes of electronically stored information. Contact her at klavelle@kanghaggerty.com.

Reprinted with permission from the October 26, 2023 edition of “The Legal Intelligencer” © 2023 ALM Media Properties, LLC. All rights reserved. Further duplication without permission is prohibited, contact 877-257-3382 or reprints@alm.com.

In the August 10, 2023 Edition of The Legal Intelligencer, Kelly Lavelle wrote “Beware of Ethical Issues in Today’s E-Discovery Landscape.“

Ethical issues in e-discovery arise due to the unique challenges and the complex nature of electronic data. The ethical challenges presented demand careful consideration and require lawyers to remain competent in emerging technology and the implications on e-discovery.

Under the American Bar Association’s Model Rules of Professional Conduct, attorneys must provide competent representation to a client. Model Rule 1.1 provides that competent representation requires the legal knowledge, skill, thoroughness, and preparation reasonably necessary for the representation. In 2012, the ABA amended this rule to highlight that an attorney’s ethical duty of competence includes a reasonable understanding of the benefits and risks associated with relevant technology. Notably, Comment 8 to Model Rule 1.1 emphasizes the need for lawyers to stay abreast of changes in the law and its practice, particularly those pertaining to technology. The comment clarifies that Rule 1.1 should be interpreted to mean that attorneys must maintain technological competence. Although the amendment did not introduce new obligations, it serves as a reminder to lawyers that they should remain aware of emerging technology as part of their ethical responsibility to remain competent.

Another important aspect of ethics in e-discovery relates to the supervision of attorneys in dealing with electronically stored information. The Model Rules of Professional Conduct impose ethical responsibilities upon both supervising and subordinate lawyers. Model Rule 5.1 provides that lawyers with direct supervisory authority must make reasonable efforts to ensure that subordinate lawyers adhere to the Rules of Professional Conduct. Supervising lawyers may be held responsible for a subordinate lawyer’s violation of the rules of professional conduct. This responsibility includes instances where the supervising attorney orders, ratifies, or fails to take remedial action when they are aware of unprofessional conduct at a time when its consequences can be avoided or mitigated.

Subordinate lawyers also have ethical responsibilities even when they act at the direction of a supervising attorney. However, Model Rule 5.2 acknowledges that a subordinate lawyer does not violate the Rules of Professional Conduct if that lawyer acts in accordance with a supervisory lawyer’s reasonable resolution of an arguable question of professional duty. In the complex world of e-discovery, partners can no longer take a hands-off approach and rely on new associates or paralegals for tasks involving electronically stored data. Attorneys may need to retain a technology expert or other consultants to aid in the process of e-discovery, which can give rise to additional ethical concerns, particularly regarding confidentiality.

The form of production of documents and electronically stored data also poses ethical considerations in e-discovery. Under Rule 34 of the Federal Rules of Civil Procedure, a producing party must produce documents in the form they are ordinarily maintained or in a reasonably usable form. This ensures that the documents are searchable or sortable by metadata fields. Further, Rule 34 prohibits simply dumping large quantities of unrequested materials onto the discovering party along with the items sought. Data dumping in e-discovery with the intention of hiding relevant information is an ethical violation. Submitting a single PDF file that contains the entire production is the electronic equivalent of a paper document dump. This results in a file that cannot be searched or sorted by metadata fields and causes undue burden upon the receiving party. It is unlikely that the original documents were kept as a single PDF file in the ordinary course of business, and the form lacks the organization and labeling required by Rule 34. Further, a single PDF file is an inappropriate and impractical form for e-discovery because of the large file size and lack of metadata. Courts have granted motions for sanctions when parties produced emails or discovery as a single PDF file, emphasizing the need for reasonable and usable forms of production.

Another paramount ethical responsibility for lawyers in e-discovery is the protection of confidential client information. Electronic discovery greatly increases the volume of information that must be reviewed for privilege. In addition, with the production of electronically stored data, there is the unique issue of possible privileged information appearing in metadata. Model Rule 1.6 governs a lawyer’s duty of confidentiality. Rule 1.6 provides that lawyers have an ethical duty to take reasonable measures to protect a client’s confidential information from inadvertent or unauthorized disclosure. However, Comment 18 clarifies that inadvertent disclosure of client information does not violate the rule if the lawyer has made efforts to prevent the disclosure.

To mitigate the risk of negative consequences arising from inadvertent disclosure under Model Rule 1.6, lawyers should carefully consider the protective measures afforded by Federal Rule of Evidence 502(d). This rule allows a federal court to enter an order known as a 502(d) order granting parties the ability to protect privileged materials from being inadvertently disclosed during the discovery process. Rule 502(d) provides that unintentional disclosure of materials protected under the attorney-client privilege or attorney work product doctrine shall not result in waiver. Unlike under Rule 502(b), a 502(d) order does not impose the requirement that the producing party took “reasonable steps to prevent disclosure” to establish nonwaiver.

In conclusion, ethical considerations are fundamental to navigating e-discovery responsibly. Adhering to ethical principles not only ensures that lawyers provide competent representation and protect client confidentiality but also signifies a commitment to staying abreast of technological advances on e-discovery. As technology evolves, lawyers must prioritize ongoing education and training to remain proficient in e-discovery practices and meet their ethical obligations.

Kelly A. Lavelle is an associate at Kang Haggerty. She focuses on e-discovery and information management, from preservation and collection to review and production of large volumes of electronically stored information. Contact her at klavelle@kanghaggerty.com.

Reprinted with permission from the August 10, 2023 edition of “The Legal Intelligencer” © 2023 ALM Media Properties, LLC. All rights reserved. Further duplication without permission is prohibited, contact 877-257-3382 or reprints@alm.com.