Important Posts – E-Discovery LLC https://www.ediscoveryllc.com Mediation of E-Discovery Disputes Sat, 10 Oct 2026 23:59:42 +0000 en-US hourly 1 Three More A.I. Protective Orders https://www.ediscoveryllc.com/three-more-a-i-protective-orders/ Fri, 09 Oct 2026 08:30:52 +0000 https://www.ediscoveryllc.com/?p=5617 […]]]> I have written a series of posts suggesting that AI protective orders are becoming the standard of care.  See A.I. Protective Order by Consent in Google Case (Sep. 13, 2026).

The jointly requested A.I. protective order in Hoffman v. Univ. of Nebraska Medical Ctr., 2026 WL 2969621 (D. Neb. Oct. 2, 2026), states:

Artificial Intelligence. Qualified Recipients shall not, without the Producing Party’s express written consent, upload, submit, or otherwise provide Confidential Discovery Material (or any information extracted therefrom) or any deposition testimony taken in this matter to any open-source artificial intelligence platform or service including, but not limited to, platforms or services that use or assemble uploaded information to train or improve machine-learning models. This prohibition applies regardless of whether the artificial intelligence platform or service represents it will maintain the confidentiality of information submitted by the user. The parties and their counsel are not prohibited from uploading, submitting, or otherwise providing Confidential Discovery Material (or information extracted therefrom) or any deposition testimony taken in this matter to a closed-source artificial intelligence platform or service, including Harvey, Westlaw, LexisNexis, Servient’s AI Canvas, or any other closed-source artificial intelligence platform or service agreed to by the parties.

In ANR Pipeline Co., LLC v. B&B Metal Processing Co., Inc., 2026 WL 2970050 (E.D. Wisc. Oct. 2, 2026), the court wrote:

On September 22, 2026, the parties filed a joint motion for the entry of a protective order, with a stipulated proposed order…. The parties request that the Court enter such an order to “prevent public disclosure of nonpublic confidential technical, commercial, or business information that may be exchanged in discovery.” … Federal Rule of Civil Procedure Rule 26(c) allows for an order “to protect a party or person from annoyance, embarrassment, oppression, or undue burden or expense” including “requiring that a trade secret or other confidential research, development, or commercial information … be revealed only in a specified way.” Fed. R. Civ. P. 26(c)(1)(G); see also Civ. L.R. 26(e).

Protective orders are an exception to the general rule that pretrial discovery must occur in the public eye…. Litigation must be conducted in public to the maximum extent consistent with respecting trade secrets … and other facts that should be held in confidence….

Nonetheless, the Court can enter a protective order if the parties have shown good cause and that the order is narrowly tailored to serve that cause…. The Court can find that even broad, blanket orders are narrowly tailored and permissible when it finds that two factors are satisfied: (1) that the parties will act in good faith in designating the portions of the record that should be subject to the protective order; and (2) that the order explicitly allows the parties to the case and other interested members of the public to challenge the sealing of documents….

The Court finds that the parties have requested the protective order in this action in good faith. The parties report that this case will entail the disclosure of confidential technical information about the parties…. Thus, the Court is satisfied that there exists a sufficient basis for the requested protective order. [cleaned up].

However, the court modified the parties’ request to establish parameters for the use of A.I. as it pertains to confidential documents.  Id. at *1.  The order states:

A receiving party may use AI tools in connection with discovery materials produced in this action only if the AI tool is operated in a secure environment and is subject to enforceable contractual terms that (a) prohibit the provider from retaining, using, disclosing, selling, or using the materials to train, improve, or develop any AI system; (b) prohibit the materials from being made publicly available or accessible to any other customer or third party; and (c) require commercially reasonable administrative, technical, and physical safeguards to protect the confidentiality of the materials. Discovery materials, whether designated CONFIDENTIAL or ATTORNEYS’ EYES ONLY, shall not be entered into any publicly available or consumer-based AI platform. Any use of AI tools must remain consistent with this Order and with the requirement that discovery materials be used solely for purposes of this litigation.

Id. at *5.

A protective order was also entered by consent in U.S.A. v. Amanuel, 2026 WL 2964210 (S.D.N.Y. Oct. 1, 2026):

Restrictions on Use of Artificial Intelligence Tools to Process Disclosure Materials.

a.  “AI tool” means any automated system that uses machine learning, or similar techniques to process inputs and generate outputs, recommendations, or predictions, including but not limited to large language models, generative AI services, or AI-assisted software tools, whether cloud-based or otherwise.

b.  The defense team will not submit Disclosure Materials to a publicly accessible version of an AI tool (e.g., ChatGPT, Claude, Grok, Gemini, Copilot, Perplexity, Midjourney, Canva). The defense team will not submit Disclosure Materials to an AI tool for which the AI tool provider or vendor (e.g., OpenAI, Anthropic, Microsoft, Google) uses submitted data for its own model training, allows submitted data to be publicly accessed, discloses submitted data to third parties, or, except as specified below, retains submitted data. Publicly accessible AI tools pose unique risks to the security and integrity of Disclosure Materials, given the practical inability to claw back or delete data once it has been incorporated into a model.

c. The defense may submit Disclosure Materials to an AI tool (i) that maintains the confidentiality of Disclosure Materials; (ii) that will not expose any Disclosure Materials to third parties not authorized under this Protective Order to receive such materials; (iii) that will not retain or use any Disclosure Materials for model training; and (iv) all Disclosure Materials will be removed from the AI tool(s) at the conclusion of this case.

Some prior posts are:

This blog was initially posted on  Electronic Discovery Reference Model.

UPDATE:

White v. Chime Financial, Inc., 2026 WL 3000904 (W.D. Wash. Oct. 6, 2026)(stipulated):

USE OF ARTIFICIAL INTELLIGENCE
Should a Party elect to utilize artificial intelligence (“AI”) to assist in reviewing, analyzing, or summarizing discovery material produced or exchanged in this litigation, the Party shall take all necessary steps to ensure that the application, service, or analytical software is fully containerized. “Fully containerized,” as used in this Order, means an AI tool that does not retain the substance of a prompt or documents reviewed, share the substance of a prompt or documents reviewed for training of large language models, or use the substance of a prompt or documents reviewed in any other matter or inquiry other than this litigation. For the avoidance of doubt, this restriction expressly applies to the use of non-containerized advanced large language models (such as publicly available large language models), generative AI tools, and other advanced AI systems, including, but not limited to, OpenAI, Gemini, LLAMA, MidJourney, and Stable Diffusion, but this provision does not limit the use of services leveraging the technology underlying these generative AI tools in a fully containerized environment, including, but not limited to, Copilot Harvey, Relativity aiR, DISCO Cecelia, Everlaw AI, Syllo, Alchemy, Lexis+ AI, Epiq AIDA, Lighthouse AI, Westlaw AI, ChatGPT Enterprise, Microsoft 365 Copilot Enterprise, Claude Enterprise, NotebookLM Pro and Ultra, and Gemini Pro and Ultra. Before submitting any Protected Material to a fully containerized AI tool, a receiving party shall ensure that it (or its vendor) can delete all such Protected Material from the AI tool at the conclusion of this matter, including any derivative information stored within the tool. The obligations and restrictions of this paragraph apply even where the Protected Material has been anonymized.

U.S.A.  v. Lockhart, 2026 WL 3003727 (S.D.N.Y.  Oct. 6, 2026)(by consent):

Restrictions on Use of Artificial Intelligence Tools to Process Disclosure Materials.

a. “AI tool” means any automated system that uses machine learning, or similar techniques to process inputs and generate outputs, recommendations, or predictions, including but not limited to large language models, generative AI services, or AI-assisted software tools, whether cloud-based or otherwise.

b. The defense team will not submit Disclosure Materials to a publicly accessible version of an AI tool (e.g., ChatGPT, Claude, Grok, Gemini, Copilot, Perplexity, Midjourney, Canva). The defense team will not submit Disclosure Materials to an AI tool for which the AI tool provider or vendor (e.g., OpenAI, Anthropic, Microsoft, Google) uses submitted data for its own model training, allows submitted data to be publicly accessed, discloses submitted data to third parties, or, except as specified below, retains submitted data. Publicly accessible AI tools pose unique risks to the security and integrity of Disclosure Materials, given the practical inability to claw back or delete data once it has been incorporated into a model.

*2 c. The defense may submit Disclosure Materials to an AI tool (i) that maintains the confidentiality of Disclosure Materials; (ii) that will not expose any Disclosure Materials to third parties not authorized under this Protective Order to receive such materials; (iii) that will not retain or use any Disclosure Materials for model training; and (iv) all Disclosure Materials will be removed from the AI tool(s) at the conclusion of this case.

d. The Government will not submit any materials disclosed by the defense pursuant to Federal Rules of Criminal Procedure 26.2, 32.1 or other defense disclosure obligations (“Defense Materials”) to a publicly accessible version of an AI tool. The Government will not submit Defense Materials to an AI tool for which the AI tool provider or vendor uses submitted data for its own model training, allows submitted data to be publicly accessed, discloses submitted data to third parties, or, except as specified below, retains submitted data.

e. The Government may submit Defense Materials to an AI tool (i) that maintains the confidentiality of Defense Materials; (ii) that will not expose any Defense Materials to third parties not authorized under this Protective Order to receive such materials; (iii) that will not retain or use any Defense Sealed Materials for model training; and (iv) all Defense Materials will be removed from the AI tool(s) at the conclusion of this case.

U.S.A. v. Santos, 2026 WL 3003653 (Oct. 6, 2026)(same, by consent); U.S.A. v. Robinson, 2026 WL 3003677 (Oct. 6, 2026)(same).

U.S.A. v. Peplow, 2026 WL 3026474 (E.D. Cal. Oct. 8, 2026)(stipulation):

Artificial Intelligence Tools
15. No person or entity authorized to have access to protected material under the terms of the requested order shall input, transmit, upload, submit, quote, feed, process, generate output from, or otherwise expose any protected material received pursuant to the requested order to any artificial intelligence (“AI”) tool absent the prior written consent of the government or an order of the Court following a properly noticed motion to which the government has an opportunity to respond, unless that AI tool—

a) is an enterprise-grade platform that counsel for the defendant has licensed;
b) is subject to a binding written agreement that (i) requires the provider to keep all user-supplied data strictly confidential, and (ii) expressly prohibits the provider from using such data for training, fine-tuning, product improvement, or any purpose other than providing the contracted-for services; and
c) employs technical and organizational security measures reasonably designed to prevent any unauthorized access, disclosure, or use of protected material.

16. The obligations and restrictions of this section apply even where the data or the protected material has been anonymized. “AI tool” means any automated system that uses statistical modeling, machine learning, or similar techniques to process inputs and generate outputs, recommendations, or predictions, including but not limited to large language models, generative AI services, or AI-assisted software tools, whether cloud-based or otherwise.

17. By participating in this agreement, counsel for the defendant certifies: (i) they have implemented reasonable measures to ensure, if using any AI tool, it will maintain the protected discovery’s confidentiality as required by this Agreement and (ii) they will ensure all protected discovery is deleted from the tool once this case concludes.

18. Under no circumstances will any member of the defense team submit protected material to a publicly accessible AI system that retains and uses submitted data to train models. Such AI tools pose unique risks to the security and integrity of protected material, given the practical inability to claw back or delete data once it has been incorporated into a model.

U.S.A. v. Sarris, 2026 WL 2937892, at *2 (S.D.N.Y.  Sep 30, 2026)(by consent).

]]> Should There Be an “A.I. Exception” to Liberal Construction of Pro Se Pleadings? https://www.ediscoveryllc.com/should-there-be-an-a-i-exception-to-liberal-construction-of-pro-se-pleadings/ Sat, 26 Sep 2026 08:57:12 +0000 https://www.ediscoveryllc.com/?p=5596 […]]]> Pro se pleadings are entitled to liberal construction.  One court has repeatedly suggested, but not held, that the liberal construction rule should be revisited in the age of A.I.  Hickam v. Chesterfield Co. School Bd., 2026 WL 2861611 (E.D. Va. Sep. 23, 2026)(Young, J.).  Litigants opposing a pro se Complaint that appears to have been prepared with GenAI, may wish to consider Judge Young’s suggestion.

To the same effect, see Almudhafer v. Spotsylvania Cnty. Pub. Schs., 2026 WL 49654, at n. 2 (E.D. Va. Jan. 7, 2026)(Young, J.); Almudhafer v. Spotsylvania Volunteer Rescue Squad, 2026 WL 49652, at n. 3 (E.D. Va. Jan. 7, 2026)(Young, J.).  Another decision states:

The Court respectfully proposes that the time may be near for an exception to the Erickson liberal-construction rule, where a pro se individual relies on AI to draft pleadings and thus blurs the line between what is a good faith pro se assertion of an actionable claim and what is a computer-generated morass that only serves to waste court time and resources.

Mitchel v. Stellantis Fin. Servs., Inc., 2025 WL 2676569, at n. 6 (E.D. Va. Sept. 18, 2025)(Young, J.).

In Hickam, among other things, the unrepresented plaintiff made a “Motion for Leave to File Second Amended Complaint…, which is accompanied by a 121-page proposed Second Amended Complaint.”

The court wrote: “Based on the Court’s inherent power to manage its docket, and mindful of the requirements set forth in the Federal Rules of Civil Procedure to which all parties, including those proceeding pro se, are bound, the Court will sua sponte dismiss without prejudice Plaintiff’s First Amended Complaint for failure to comply with Federal Rule of Civil Procedure 8. Furthermore, the Court will deny without prejudice Plaintiff’s Motion for Leave to File Second Amended Complaint and direct Plaintiff, should he desire to continue this matter, to submit a proposed Second Amended Complaint that complies with Federal Rule of Civil Procedure 8.”

In part, the court explained that “to determine the viability of Plaintiff’s claims, the Court would have to engage in the improper task of sifting through 416 paragraphs to piece together a cogent timeline of events in order for the Court to assess how each of Plaintiff’s claims relates to each of the Defendants.”

The Hickam court recognized that a pro se complaint is “to be liberally construed” and “held to less stringent standards than formal pleadings drafted by lawyers,” citing Erickson v. Pardus, 551 U.S. 89, 94 (2007) (internal quotation marks omitted).

In a footnote, the court added:

The Court notes that Erickson’s liberal-construction requirement for pro se pleadings predates the advent of artificial intelligence (“AI”) drafting tools, which are being used with increasing prevalence by pro se parties in particular.…  Such tools both increase pro se litigants’ ability to draft voluminous pleadings and increase the odds that such pleadings contain fractured assertions and “hallucinated” legal propositions, which courts must wade through in construing claims…. While its analysis does not ultimately turn on this point, the Court notes that several of Plaintiff’s filings appear to carry the hallmarks of AI drafting assistance beyond that to which Plaintiff certifies. [emphasis added].

In the Spotsylvania Volunteer Rescue Squad decision, the court added: “[I]t respectfully proposes that the time may be near for an exception to the Erickson liberal-construction rule, where a pro se individual relies on AI to draft pleadings and thus blurs the line between what is a good faith pro se assertion of an actionable claim and what is a computer generated morass that only serves to waste court time and resources.”  2026 WL 49652, at n. 3.

The liberal construction rule has been recently and frequently cited. For example: “When a party is pro se, the court will construe her submissions ‘liberally to raise the strongest arguments that they suggest.’” Shah v. Bhagat, 2026 WL 2859875, at *3 (S.D.N.Y. Sept. 23, 2026)’

It will be interesting to see if an A.I. exception to the rule of liberal construction begins to emerge.

This blog was initially posted on  Electronic Discovery Reference Model.

]]> Another AI Protective Order https://www.ediscoveryllc.com/another-ai-protective-order/ Wed, 16 Sep 2026 13:46:12 +0000 https://www.ediscoveryllc.com/?p=5549 […]]]> The following Stipulated Protective Order was entered in Rapacon v. Abbott  Laboratories, 2026 WL 2722543 (N.D. Cal. Sep. 15, 2026):

  1. USE OF GENERATIVE AI TOOLS

“CONFIDENTIAL” Information or Items shall not be submitted to any Open Generative AI tool (e.g., Chat GPT) or any substantially similar tool that is available to the public. Providing “CONFIDENTIAL” Information or Items to an Open Generative AI tool is considered disclosure to a third party. For purposes of this Protective Order, “Open Generative AI tool” means an artificial intelligence system that may be accessed by the public, or that allows for the underlying code and materials to be accessed by the public.

The Parties may only submit “CONFIDENTIAL” Information or Items to a Permitted Generative AI Tool. For purposes of this Protective Order, a “Permitted Generative AI Tool” includes the use of enterprise AI tools that: (i) restrict access to authorized users; (ii) do not use customer data to train, refine, fine-tune, or improve publicly available models; (iii) provide reasonable retention and deletion controls; and (iv) maintain commercially reasonable security and confidentiality protections. For the avoidance of doubt, enterprise legal and productivity platforms that satisfy the foregoing requirements, including Thomson Reuters CoCounsel, Microsoft 365 Copilot, and similar enterprise tools, are permitted.

For more information on A.I. Protective Orders, please visit:

UPDATE:  ZL Technologies, Inc. v. KLDiscovery Ontrack, LLC, 2026 WL 2731631, at *9 (S.D.N.Y. Sep. 16, 2026):

Use of Artificial Intelligence Tools

(a) Scope: To protect the confidentiality and security of all information disclosed or produced in this proceeding (“Discovery Information”), any Party receiving Discovery Information from another Party (“Receiving Party”) shall comply with the following requirements governing the use of artificial intelligence (“AI”) tools with such information.

(b) Permitted AI Use: A Receiving Party may use AI tools to process Discovery Information solely for purposes of this proceeding, provided that the AI tool and its use collectively satisfy all of the following requirements:

i.  Restricted, Enterprise Environment: The AI tool is used pursuant to a written enterprise or professional agreement and is deployed within a secure, access-controlled environment.

ii.  No Model Training or External Use: Discovery Information is not used to train, fine-tune, improve, develop, benchmark, or otherwise contribute to any AI model or service accessible outside the Receiving Party’s environment, except to the limited extent necessary to provide the requested functionality for this proceeding.

iii. Data Retention and Deletion: Within 30 days after final disposition of this action, Discovery Information retained by the AI tool shall be destroyed or caused to be destroyed to the extent reasonably possible.

iv.  Security Safeguards: The AI tool is subject to technical and contractual safeguards reasonably designed to protect Discovery Information against unauthorized access, use, or disclosure, including encryption in transit and at rest and appropriate access controls.

(c) No Backdoor Access: Nothing in Section 23 permits a Party, Agent, Expert, or other person that is not able to access Confidential Discovery Information or Highly Confidential – Attorneys’ Eyes Only Information under this Order to use AI tools to query, analyze, search or otherwise process such information.

(d) Responsibility and Attribution: Each Receiving Party is responsible for compliance with this Order by its counsel, experts, consultants, vendors, or other agents using AI tools on its behalf.

(e) Attorney Work Product: Use of an AI tool shall not waive or diminish any applicable privilege or work-product protection, and prompts, instructions, workflows, chat histories, and outputs shall be treated the same as analogous attorney work product created without the use of AI tools.

UPDATE: U.S. v. Perez-Feliz, 2026 WL 2754823 (S.D.N.Y. Sep. 17, 2026)(consent order):

Restrictions on Use of Artificial Intelligence Tools to Process Disclosure Materials.

a. “AI tool” means any automated system that uses machine learning, or similar techniques to process inputs and generate outputs, recommendations, or predictions, including but not limited to large language models, generative AI services, or AI-assisted software tools, whether cloud-based or otherwise.

b. The defense team will not submit Disclosure Materials to a publicly accessible version of an AI tool (e.g., ChatGPT, Claude, Grok, Gemini, Copilot, Perplexity, Midjourney, Canva). The defense team will not submit Disclosure Materials to an AI tool for which the AI tool provider or vendor (e.g., OpenAI, Anthropic, Microsoft, Google) uses submitted data for its own model training, allows submitted data to be publicly accessed, discloses submitted data to third parties, or, except as specified below, retains submitted data.

c. The defense may submit Disclosure Materials to an AI tool (i) that maintains the confidentiality of Disclosure Materials; (ii) that will not expose any Disclosure Materials to third parties not authorized under this Protective Order to receive such materials; (iii) that will not retain or use any Disclosure Materials for model training; and (iv) all Disclosure Materials will be removed from the AI tool(s) at the conclusion of this case.

UPDATE: U.S. v. Montes, 2026 WL 2824059, at *1 (S.D.N.Y. Sep. 21, 2026)(by consent); U.S. v. Hawkins 2026 WL 2825014, at *2 (S.D.N.Y. Sep. 21, 20260(same).

a. “AI tool” means any automated system that uses machine learning, or similar techniques to process inputs and generate outputs, recommendations, or predictions, including but not limited to large language models, generative AI services, or AI-assisted software tools, whether cloud-based or otherwise.

b. The defense team will not submit Disclosure Materials to a publicly accessible version of an AI tool (e.g., ChatGPT, Claude, Grok, Gemini, Copilot, Perplexity, Midjourney, Canva). The defense team will not submit Disclosure Materials to an AI tool for which the AI tool provider or vendor (e.g., OpenAI, Anthropic, Microsoft, Google) uses submitted data for its own model training, allows submitted data to be publicly accessed, discloses submitted data to third parties, or, except as specified below, retains submitted data. Publicly accessible AI tools pose unique risks to the security and integrity of Disclosure Materials, given the practical inability to claw back or delete data once it has been incorporated into a model.

c. The defense may submit Disclosure Materials to an AI tool (i) that maintains the confidentiality of Disclosure Materials; (ii) that will not expose any Disclosure Materials to third parties not authorized under this Protective Order to receive such materials; (iii) that will not retain or use any Disclosure Materials for model training; and (iv) all Disclosure Materials will be removed from the AI tool(s) at the conclusion of this case.

d. No person or entity authorized to have access to Disclosure Materials under the terms of this Order shall input, transmit, upload, process, generate output from, or otherwise expose any Disclosure Materials received pursuant to this Protective Order to any AI tool without prior written notice to, and corresponding receipt of acknowledgement from, the Government.

UPDATE: U.S.A. v Amanuel, 2026 WL 2972618 (S.D.N.Y. Oct. 2, 2026)(by consent).

Restrictions on Use of Artificial Intelligence Tools to Process Disclosure Materials.

a. “AI tool” means any automated system that uses machine learning, or similar techniques to process inputs and generate outputs, recommendations, or predictions, including but not limited to large language models, generative AI services, or AI-assisted software tools, whether cloud-based or otherwise.

b. The defense team will not submit Disclosure Materials to a publicly accessible version of an AI tool (e.g., ChatGPT, Claude, Grok, Gemini, Copilot, Perplexity, Midjourney, Canva). The defense team will not submit Disclosure Materials to an AI tool for which the AI tool provider or vendor (e.g., OpenAI, Anthropic, Microsoft, Google) uses submitted data for its own model training, allows submitted data to be publicly accessed, discloses submitted data to third parties, or, except as specified below, retains submitted data. Publicly accessible AI tools pose unique risks to the security and integrity of Disclosure Materials, given the practical inability to claw back or delete data once it has been incorporated into a model.

c. The defense may submit Disclosure Materials to an AI tool (i) that maintains the confidentiality of Disclosure Materials; (ii) that will not expose any Disclosure Materials to third parties not authorized under this Protective Order to receive such materials; (iii) that will not retain or use any Disclosure Materials for model training; and (iv) all Disclosure Materials will be removed from the AI tool(s) at the conclusion of this case.

d. The Government will not submit Defense Materials to a publicly accessible version of an AI tool (e.g., ChatGPT, Claude, Grok, Gemini, Copilot, Perplexity, Midjourney, Canva). The Government will not submit Defense Materials to an AI tool for which the AI tool provider or vendor (e.g., OpenAI, Anthropic, Microsoft, Google) uses submitted data for its own model training, allows submitted data to be publicly accessed, discloses submitted data to third parties, or, except as specified below, retains submitted data.

e. The Government may submit Defense Materials to an AI tool (i) that maintains the confidentiality of Defense Materials; (ii) that will not expose any Defense Materials to third parties not authorized under this Protective Order to receive such materials; (iii) that will not retain or use any Defense Sealed Materials for model training; and (iv) all Defense Materials will be removed from the AI tool(s) at the conclusion of this case.

 

 

 

 

 

 

]]> Proposal to Use Unilaterally-Designed A.I. for Search Was Rejected https://www.ediscoveryllc.com/proposal-to-use-unilaterally-designed-a-i-for-search-was-rejected/ Tue, 15 Sep 2026 19:25:55 +0000 https://www.ediscoveryllc.com/?p=5546 […]]]> The court in Goldstein v. RTX Corp., 2026 WL 2690139 (D. Del. Sep. 14, 2026), rejected a proposal to use a unilaterally-designed AI tool for a search.

The case is a putative collective and class action alleging a “nationwide pattern, practice, and/or policy of discriminating against older workers … in their hiring processes.”  At issue was the manner of collective notice procedures.

The parties raise four primary disputes regarding the proposed collective notice procedures: (1) whether notice should be authorized for applicants of the non-RTX Defendants, (2) how to determine which job postings qualify as “Recent Graduate Positions,” (3) how to identify putative collective members, and (4) whether a website to return consent forms should be publicly available or password protected.

Id. at *2.

This post focuses on No. 2. The court wrote:

Next, the parties dispute how to determine which job postings qualify as “Recent Graduate Positions” reserved for “those who have graduated in the prior year or two (or who will soon graduate), or applicants with college degrees who have less than 12 or 24 months of work experience.” … Plaintiffs propose negotiating search terms with Defendants that target experience and recent graduate limitations…. In contrast, Defendants suggest filtering positions in their Workday database based on several data fields and then training an artificial intelligence model to identify job descriptions meeting Plaintiffs’ definition of “Recent Graduate Positions.”

Id. at *3 (emphasis added).

The court adopted Defendants’ proposal to employ the Workday database fields.  However, addressing the A.I. proposal, the court wrote:

Plaintiffs’ proposal to negotiate appropriate search terms targeting experience and recent graduate limitations is ADOPTED-IN-PART, and Defendants’ competing proposal to train an artificial intelligence model is REJECTED. Defendants contend that the Workday database does not have a field that can cleanly isolate Recent Graduate Positions, and the requirements for these positions are phrased differently, posing the risk of an underinclusive search….  Plaintiffs note that they “requested the sample of job postings Defendants reviewed in reaching that conclusion[,]” but “Defendants have not produced any sample.” … A collaborative process to agree on search terms is preferable to the unilateral training of an artificial intelligence model, which is no less likely to raise issues of under-inclusiveness. However, Plaintiffs’ proposal is REJECTED to the extent that they seek to compel Defendants to produce a 30% sample of Recent Graduate job postings across the relevant time period. Plaintiffs provide no authority in support of this proposal, which is effectively a motion to compel discovery. Therefore, IT IS ORDERED that the parties shall meet and confer on search terms to employ in the search process within fourteen (14) days of this Memorandum Order.

Id. at *4 (emphasis added). The court ordered that:

Defendants’ proposals to: (i) employ the Workday database fields identified in their supplemental submission to identify which positions quality as “Recent Graduate Positions,” and (ii) exclude from the realm of Recent Graduate Positions any positions open to recent master’s graduates or “degree equivalency” positions open to either recent college graduates or those with equivalent work experience are ADOPTED. Plaintiffs’ proposal to negotiate appropriate search terms targeting experience and recent graduate limitations to further identify Recent Graduate Positions is ADOPTED-IN-PART, and Defendants’ competing proposal to train an artificial intelligence model is REJECTED. Accordingly, IT IS ORDERED that the parties shall meet and confer to negotiate appropriate search terms within fourteen (14) days of this Memorandum Order.

Id. at *5 (emphasis added).

]]> Phil Favro Discusses Deepfakes and Authentication https://www.ediscoveryllc.com/phil-favro-discusses-deepfakes-and-authentication/ Thu, 03 Sep 2026 09:00:37 +0000 https://www.ediscoveryllc.com/?p=5485 […]]]> Phil Favro has posted New Court Case Exemplifies Evidentiary Challenges with Deepfakes (Aug. 13, 2026), discussing both sides of authentication of evidence challenged as a deepfake. Phil uses the majority and dissenting opinions in U.S. v. Belt, 181 F.4th 931 (8th Cir. 2026), as an example.

In Belt, in brief summary, a government agent obtained Ring camera video of the crime.  On the one hand, the “video appeared to capture several aspects of the crime such as shouting, the assaults, a fire on the victim’s property, defendants’ vehicle, and the eventual arrival of law enforcement,” among other things.  Id.  That is typical authentication evidence.

On the other hand, Phil explained:  “The video also included several gaps ranging from seconds to over 22 minutes. During one of the gaps, a car ran over the victim.”  The owner of the Ring camera was not available to testify about the cause of the gaps.

The defense argued that the missing footage would have been exculpatory and that the gaps showed tampering. The trial court overruled the objection. A divided appellate panel held that the government met the “low bar” of authentication.  The majority held that the gaps went to weight, not admissibility. An en banc panel affirmed.

Phil provides great detail about the dissents.  For example, Phil wrote:

Judge Kelly criticized the majority for glossing over the circumstances surrounding the video in Belt, which differed from traditional instances where law enforcement testify about footage they generated. In Belt, the FBI agent did not create the footage, but downloaded it directly from the aunt’s Ring camera. In so doing, the agent did not obtain information about the camera make or model, the software application used, or whether the system recorded continuously or was motion activated. Without that information, the government failed to offer evidence supporting the conclusion that the camera was operating as designed….  From her perspective, the gaps impacted the video’s admissibility and not merely its weight.

Phil noted: “Judge Erickson called out the issue of deepfakes, observing that the ‘changing technological environment in which we live’ calls for a stricter gatekeeping function by trial courts given the reality of AI-generated videos.”

Phil also suggests that proponents need to be prepared to show the “provenance” of a video and wrote: “One way to do so is by collecting and preserving original native files rather than relying on informal file transfers like the download that took place in Belt.”  He also suggests documenting the make and model of the recording hardware, the software version, a chain of custody log, “and the operational parameters (such as whether the device records continuously or uses motion-activation sensors).”

Phil explains that: “Parties opposing the introduction of deepfake videos should ground their accusations in fact-specific evidence. This may very well require the retention of experts to evaluate the quality and nature of the recording at issue. In addition, the opponent (and its expert) may need to inspect the underlying file structure for the video to assess any number of issues, including whether the application permits media editing and whether the footage or feed was in some way manipulated.”

Phil’s suggestions are excellent, as they always are. Congratulations to Phil Favro on the Opening Favro Law PLLC (Jun. 16, 2025).  He is an amazing attorney, person, and resource.

One interesting authentication case is described in Evidence Sufficient to Demonstrate that Audio Recording Was Not a Deepfake (Mar. 23, 2026). I won’t repeat it all here.  The proponent authenticated a voice mail challenged as a deepfake with an affidavit from the company that owned the voicemail system, stating that it was accurate and unaltered, and with the lay proponent’s own affidavit stating voice recognition and additional details.  The party claiming that the recording was a deepfake refused to testify, and that said a lot.

There are several other great resources, the National Center for State Courts has published “bench cards.” Deepfakes – National Center for State Courts (Mar. 6, 2026).

Craig Ball has posted a wonderful guide.  Book Review: Craig Ball, “Forensic Tells: The Litigator’s Guide to Detecting Deepfakes and Authenticating Digital Evidence” (Mar. 7, 2026).

And, there are examples of forensic examination exposing deepfakes. Deepfakes Uncovered – iPhone 6 Could Not Have Captured the A.I.-Generated Evidence (Sep. 25, 2025)(“Here’s the problem for [plaintiff] Maridol Mendones: Apple did not introduce Apple Intelligence until iOS18 and required an iPhone 16, iPhone 15 Pro, or iPhone 15 Pro Max.”).

The Supreme Court of Maryland has answered affirmatively the question of Can a witness authenticate a video if the video contains images that the witness did not see? (Aug. 16, 2024).

Generally, video and photos can be authenticated by either the “pictorial evidence” or “silent witness” theory.[1]  “Pictorial evidence” generally requires a witness with knowledge.

The “silent witness” method “allows for authentication by the presentation of evidence describing a process or system that produces an accurate result. Specifically, a witness can testify to the type of equipment or camera used, its general reliability, the quality of the recorded product, the process by which it was focused, or the general reliability of the entire system.” Authentication of Surveillance Video by Lay Witness Under Silent Witness Doctrine (Dec. 9, 2024)(citation omitted).

That is precisely the technique Phil was describing.  His advice is spot on.

Maryland has also permitted authentication of a “composite” video. Is a “Composite” Video Admissible and Can a Police Officer “Narrate” It at Trial? – Part 2 of 2 (Sep. 1, 2024)(neither of the detectives witnessed the events about which they testified; however, they confirmed many facts in the video).

In Maryland, the Trial Court is a “Gatekeeper” But Not an “Armed Guard” (Jun. 25, 2022).

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[1] Video may be authenticated as a business record, by circumstantial evidence, or by a combination of methods, according to the Supreme Court of Maryland, and that list is not exhaustive.

]]> Upload of Documents to Anthropic Products Leads to Denial of Motion to Seal Record https://www.ediscoveryllc.com/upload-of-documents-to-anthropic-products-leads-to-denial-of-motion-to-seal-record/ Fri, 28 Aug 2026 13:55:32 +0000 https://www.ediscoveryllc.com/?p=5507 […]]]> Much has been written about whether use of A.I. waives the attorney-client privilege or work product protection. Tara Emory and Maura Grossman Address Protection of Attorney Prompts in “GenAI TAR” (Jul. 5, 2026); Deponent’s Use of A.I. to Answer Deposition Questions Barred; ChatGPT Was Not an Attorney (May 2, 2026); Important A.I. Work Product and Protective Order Decision (Mar. 31, 2026);  “Two Courts, Two Answers: When Does Using AI Waive Privilege?” (Mar. 3, 2026).

A court recently held that an upload to Claude waived any right to seal documents filed in court.

In Fry v. Fry, 2026 WL 2531956 (E.D. Penn. Aug. 27, 2026), the petitioner alleged that his wife had wrongfully removed their children from Germany to the U.S.  Petitioner also sought sealing of certain documents that had been filed.  They contained “personal identifiers such as social security numbers, dates of birth; financial account numbers; names of minor children; names and contact information of third-party military and medical personnel mentioned in his email correspondence and military records; prescription and medical records of Petitioner; correspondence with German officials; and details of domestic disputes between Petitioner and Respondent.”

After analyzing both the First Amendment and common law, and after in camera review, the court granted, in part, and denied, in part, the motion to seal.  It wrote in pertinent part:

With Petitioner’s renewed motion, the Court required Petitioner to submit an AI certification describing any assistance of AI that Petitioner utilized to prepare his motion…. Petitioner disclosed to the Court that he had uploaded his redacted documents to non-enterprise versions of Claude and Claude CoWork, products by third-party company Anthropic, in preparing his motion. As such, the Court finds that the full sealing of any document is not appropriate. Documents and information uploaded to Claude are processed on Anthropic’s servers, and Anthropic’s data privacy and data training pages make clear that such information is not private. See, e.g., Privacy Policy, Anthropic https://www.anthropic.com/legal/privacy (last accessed August 24, 2026); How Do You Use Personal Data in Model Training?, Anthropic, https://privacy.claude.com/en/articles/10023555-how-do-you-use-personal-data-in-model-training (last accessed August 27, 2026); see also United States v. Heppner, 820 F. Supp. 3d 292, 296 (S.D.N.Y. 2026) (holding that communications with Claude are not privileged due, in part, to Claude’s privacy policy). As such, it would be inappropriate for the Court to seal a document that has already been provided to a private, for-profit research and artificial intelligence company. [emphasis added].

 

]]> A Request for “Three-Strata Validation” Was Denied https://www.ediscoveryllc.com/a-request-for-three-strata-validation-was-denied/ Thu, 27 Aug 2026 15:32:36 +0000 https://www.ediscoveryllc.com/?p=5494 […]]]> Every search must be validated.  It is “entirely self-evident” that “ipse dixit pronouncements from lawyers unsupported by an affidavit or other showing that the search methodology was effective for its intended purpose are of little value to a trial judge.”  Victor Stanley, Inc. v. Creative Pipe, Inc., 250 F.R.D. 251, 261 (D. Md. 2008).

“Three-strata validation” was requested and rejected in In re Class Action Settlement Administration Litigation, 2026 WL 2444936 (D.D.C. Aug. 19, 2026). The parties in that case had narrowed their disputes and their “only remaining disagreement concerns how a party producing documents in discovery must validate that its productions are substantially complete.”

Plaintiffs asked for “three-strata validation.”  Defendants objected to the second and third strata.

The court explained the “three-strata” approach as:  “validation of documents coded as non-responsive, validation of documents coded as responsive, and validation of documents excluded from the universe of ESI material subject to discovery review.”

THE PARTIES AGREED TO NULL SET TESTING

The parties agreed that there is an obligation  “to confirm that responsive documents are not erroneously coded as non-responsive and omitted from their productions.” This involves review of a “statistically valid random sample” of documents coded as non-responsive. Id. at *1.

This standard practice is commonly called “elusion testing,” review of the “discard pile,” or, review of  the “null set.”  See Deal Genius, LLC v. O2COOL, LLC, 682 F. Supp. 3d 727, 734–35 (N.D. Ill. 2023) (“explaining that elusion testing, where the producing party reviews a random sample from the ‘null set’ of documents that did not hit on search terms and documents that were deemed non-responsive, is a ‘standard quality assurance practice’ that can ‘confirm the reasonableness and proportionality’ of the production”).

VALIDATION OF DOCUMENTS CODED AS RESPONSIVE – REJECTED

Defendants argued that validation of documents coded as responsive, to find false positives, was superfluous.  They asserted that Fed.R.Civ.P. 26(g) required that they certify that their response is complete and correct.  The court wrote: “Rephrased in statistical terms, producing parties must confirm that their false-negative rate falls within acceptable limits.”  In my less elegant words, a production may include nonresponsive documents; but, it cannot be a “dump truck.”

The court explained:

Review of documents marked responsive falls outside the bounds of litigants’ Rule 26(g) obligations because such review cannot identify whether documents are missing from a production, rendering it incomplete. Confirming that documents designated responsive are truly responsive reveals only the production’s false-positive rate, a proxy measure for whether the litigant has overproduced discovery material. But the Federal Rules do not prohibit parties from overproducing documents. Accordingly, this Court will not require defendants to incur additional costs re-reviewing documents that they have previously coded as responsive and intend to produce, barring claims of privilege. [emphasis in original].

VALIDATION OF DOCUMENTS EXCLUDED FROM THE UNIVERSE – REJECTED

The second strata consists of “ documents excluded from the universe of ESI material subject to discovery review.”  In other words, Plaintiffs asked for a review of documents that Defendants had not collected and that, presumably, were  not in Defendants’ litigation review platform.

The court wrote that examination of this set of documents, the “Excluded Set,” “could reveal false-negatives: responsive materials that should be produced but were erroneously omitted from the universe of materials collected for discovery review.”

However, the court responded that Plaintiffs’ request was duplicative and made too late, long after collection.  It wrote:  “Yet the Court is puzzled why plaintiffs request review of the Excluded Set after discovery review is largely complete, given that the parties also intend to review the Excluded Set for responsive material prior to beginning that review.” [emphasis in original].

The court explained that “ESI discovery generally proceeds in two phases: document collection and merits review.”  The parties had earlier “set forth agreed upon parameters for collecting the universe of documents that will be subject to merits review.”  That earlier agreement had required statistical sampling.

Insofar as the parties have agreed to statistically validate the completeness of the set of documents collected for merits review before even beginning that review, the Court finds that further validation of the Excluded Set after merits review is largely complete would be duplicative and unnecessary.

However, Plaintiffs made a different argument—so-called “substantial completeness evaluation.”  They argued that:

[T]heir proposed validation efforts “answer different questions at different points in time,” because search term validation “tests whether agreed terms are performing as intended before review begins,” while substantial completeness validation of the Excluded Set “tests whether the entire process — including all downstream coding decisions, review workflow, and production choices — resulted in a complete production at its conclusion.”

This argument was unsuccessful because the court held that “the Excluded Set is a collection of documents excluded before merits review begins and not subject to downstream coding decisions, review workflows, and production choices.”

Plaintiffs also contended that “the prevailing practice is for parties producing discovery to validate the Excluded Set both upon its creation and after merits review….”  The court noted that the authorities are split; however, it held that “the Court will not require producing parties to incur the cost and burden to re-validate the Excluded Set at the substantial completeness stage, provided that they statistically validate that documents excluded from merits review do not contain responsive material before beginning that review.”

I would add that “substantial completeness validation” of the Excluded Set could de-rail a case and mandate a “do over.”  If a sufficient number of false negatives was found in that set—and sufficiency is always debatable–presumably Defendants would have to engage in a new collection, review, and production process.

This blog was initially posted on  Electronic Discovery Reference Model

]]> Supreme Court of Maryland Denied Certiorari in Guthrie v. Vincenti https://www.ediscoveryllc.com/supreme-court-of-maryland-denied-certiorari-in-guthrie-v-vincenti/ Sat, 22 Aug 2026 12:17:35 +0000 https://www.ediscoveryllc.com/?p=5441 […]]]> Generally, I post blogs about e-discovery.  However, together with Alan Rifkin, Stuart Cherry, and Rifkin Weiner Livingston LLC, I have had the honor of representing the President of the County Council of Harford County, Maryland: in the Circuit Court; as appellee in the Appellate Court; and now in successfully opposing a request for a writ of certiorari in the Supreme Court of Maryland.

The opinion is reported at Guthrie v. Vincenti, bypass cert. denied, 490 Md. 138 (2025), subsequent opinion, 269 Md. App. 680 (2026), cert. denied, __ Md. __ (Aug. 21, 2026). The successful outcome is described in Supreme Court of Maryland Denies Cert Petition in Guthrie v. Vincenti – Rifkin Weiner Livingston LLC (Aug. 21, 2026).

For coverage in today’s Baltimore Sun, see Racquel Bazos, Maryland Supreme Court won’t hear Guthrie’s case to restore council seat.  After reporting the statement by Mr. Guthrie’s attorney, the article states:

Vincenti’s representatives disputed that claim, saying the law is clear.

“Unfortunately, Mr. Gansler continues to perpetuate an interpretation of the law that is baseless. Every judge from the trial court to the Appellate Court to the Maryland Supreme Court twice has reached the same conclusion, and that conclusion is directly contrary to Mr. Gansler‘s statement,” said Michael Berman, one of Vincenti’s attorneys, on behalf of the firm Rifkin Weiner Livingston.

“The applicable Maryland constitutional provision, which we call the clean government clause, is unambiguous and was properly applied by the courts at every level,” he said.

For prior blogs discussing my oral argument and earlier rulings, please see

]]> Another A.I. Protective Order – Part 10 https://www.ediscoveryllc.com/another-a-i-protective-order-part-10/ Fri, 21 Aug 2026 09:25:41 +0000 https://www.ediscoveryllc.com/?p=5432 […]]]> I have been posting about A.I. protective orders since last year.  This is the 10th post.  A.I. protective orders, in one form or another, are becoming the standard of care.

Basically, these orders limit use of artificial intelligence by the recipient of discovery materials.  But, they are not always fair.

Craig Ball has explained that these orders can create a double standard.  He quoted a District of Colorado decision stating “that practically speaking, and in light of the current state of AI, this provision will (at least for now) bar the parties from using most, if not all, mainstream low-to-no cost AI to process Confidential Information.”  Craig added:

If other courts follow uncritically, it will do what every prior technology-gatekeeping effort has done: widen the gap between well-funded litigants and everyone else, while delivering no meaningful improvement in data security.  My hope is that this post will shed light on a distinction without a difference so as to not hinder the use of properly configured, ‘consumer grade’ AI for processing sensitive data.

U.S. v. Dygdon, 2026 WL 2225226 (S.D.N.Y. Aug. 3, 2026), provides another example of an AI  protective order entered by consent in a criminal case.  The materials disclosed in discovery  would affect “the privacy, confidentiality and business interests of individuals and entities,” and “would risk prejudicial pretrial publicity if publicly disseminated….” The consent order states:

  1. Restrictions on Use of Artificial Intelligence Tools to Process Disclosure Materials.

    a.  “AI tool” means any automated system that uses statistical modeling, machine learning, or similar techniques to process inputs and generate outputs, recommendations, or predictions, including but not limited to large language models, generative AI services, or AI-assisted software tools, whether cloud-based or otherwise.

    b.  Under no circumstances will any member of the defense team submit Disclosure Materials to a publicly accessible AI tool, or any AI tool, that retains and uses submitted data to train models. Such AI tools pose unique risks to the security and integrity of Disclosure Materials, given the practical inability to claw back or delete data once it has been incorporated into a model.

    c.  With respect to any AI tool used by the defendant, defense counsel must be able to certify that (i) the AI tool(s) will maintain the confidentiality of any Disclosure Materials; (ii) the AI tool(s) will not expose any Disclosure Materials to third parties not authorized under this Protective Order to receive such materials; (iii) the AI tool(s) will not retain or use any Disclosure Materials for model training; and (iv) all Disclosure Materials will be removed from the AI tool(s) at the conclusion of this case.

I suggest that there is general agreement that a degree of protection of materials produced in discovery is reasonable.  Craig has some excellent suggestions, writing: “I’m not arguing for anarchy or carelessness. I’m arguing for proportionality….”

Craig lists five provisions for a “properly scoped Ai provision….” They are: 1) no training; 2) no public accessibility; 3) matter isolation; 4) deletion at conclusion; and, 5) documentation.  He adds: “Five requirements, all achievable at any budget. All providing genuine protection against the actual risks that protective orders target: unauthorized use, competitive exploitation, and ongoing exposure. Anything beyond this isn’t really protecting data. It’s protecting market position.”

I suggest that AI protective orders are now the standard of care. I agree with Craig’s well-written suggestion that “we can protect discovery materials without building a toll booth that only the well-heeled can pass through.”

I also very much appreciate Craig’s endnote: “Hat tip to my friend Michael Berman, whose frequent and excellent series of posts about AI and discovery law got me thinking about this today.”

For more on this topic, please visit:

This blog was initially posted on  Electronic Discovery Reference Model.

UPDATE:

After the first posting of this blog, an AI protective order was entered by consent in U.S.A. v. Marrow, 2026 WL 2389395 (S.D.N.Y. Aug. 17, 2026).

7. Restrictions on Use of Artificial Intelligence Tools to Process Disclosure Materials.

a. “AI tool” means any automated system that uses machine learning, or similar techniques to process inputs and generate outputs, recommendations, or predictions, including but not limited to large language models, generative AI services, or AI-assisted software tools, whether cloud-based or otherwise.

b. The defense team will not submit Disclosure Materials to a publicly accessible version of an AI tool (e.g., ChatGPT, Claude, Grok, Gemini, Copilot, Perplexity, Midjourney, Canva). The defense team will not submit Disclosure Materials to an AI tool for which the AI tool provider or vendor (e.g., OpenAI, Anthropic, Microsoft, Google) uses submitted data for its own model training, allows submitted data to be publicly accessed, discloses submitted data to third parties, or, except as specified below, retains submitted data.

c. The defense may submit Disclosure Materials to an AI tool (i) that maintains the confidentiality of Disclosure Materials; (ii) that will not expose any Disclosure Materials to third parties not authorized under this Protective Order to receive such materials; (iii) that will not retain or use any Disclosure Materials for model training; and (iv) all Disclosure Materials will be removed from the AI tool(s) at the conclusion of this case.

Additional consent cases are U.S.A. v. Spatola, 2026 WL 2351459 (S.D.N.Y. Aug. 13, 2026), U.S.A. v. Davis, 2026 WL 1333520 (S.D.N.Y. Aug. 12, 2026).  The protective order in Spatola is the same as Marrow.  The order in Davis states:

Restrictions on Use of Artificial Intelligence Tools to Process Disclosure Materials.

a.  “AI tool” means any automated system that uses statistical modeling, machine learning, or similar techniques to process inputs and generate outputs, recommendations, or predictions, including but not limited to large language models, generative AI services, or AI-assisted software tools, whether cloud-based or otherwise.

b. Under no circumstances will any member of the defense team submit Disclosure Materials to a publicly accessible AI tool, or any AI tool, that retains and uses submitted data to train models. Such AI tools pose unique risks to the security and integrity of Disclosure Materials, given the practical inability to claw back or delete data once it has been incorporated into a model.

A different A.I. order was entered by consent in U.S. v. Stamp, 2026 WL 2321897 (S.D.N.Y.  Aug. 11, 2026).  It added:

d. Any translation, transcript, summary, or other output that reveals the substance of Disclosure Material shall be treated as Disclosure Material, but draft legal briefs, counsel memoranda, and other attorney work product shall not be considered Disclosure Material irrespective of whether they were created in part through the use of an AI tool.

e. Defense counsel may permit access by AI tool provider personnel, affiliates, and subprocessors, to databases containing Disclosure Material only as reasonably necessary to provide, maintain, secure, or support the AI tool, subject to confidentiality obligations set forth herein.

UPDATE: U.S.A.v. Morell, 2026 WL 2676582, at *1 (S.DN.Y. Sep. 11, 2026).

]]> Maryland’s Digital Media Rules https://www.ediscoveryllc.com/marylands-digital-media-rules/ Thu, 20 Aug 2026 09:25:40 +0000 https://www.ediscoveryllc.com/?p=5428 […]]]> Maryland has promulgated rules expressly governing how “digital media” is entered into the court record when presented in either motions or open court. The rules also govern the record on appeal.

DIGITAL MEDIA OFFERED IN OPEN COURT

Paper exhibits are the default choice.  Maryland Rule 20-106(e)(1) states: “Unless otherwise approved by the court, a document offered into evidence as an exhibit in open court shall be offered in paper form. The document shall be appropriately marked.”

However, Maryland’s Digital Media Rule, Rule 20-106(e)(3), states: “Digital media offered in open court and included in the record pursuant to Rule 2-516, 3-516, or 4-322 shall be (A) submitted using a digital storage platform approved by the State Court Administrator and (B) referenced in the MDEC system by docket entry.”  [emphasis added].

Rule 1-202(j) defines digital media as “material in an audio, audiovisual, or video format that can be transmitted and stored electronically.”

The Rule applies to “digital media” included in the record under Rule 2-516, Rule 3-516, or Rule 4-322.  The first two Rules address civil lawsuit. Rule 4-322 applies to criminal cases.

  • In courts of general jurisdiction, the Circuit Courts, Rule 2-516(b)(1)(A) states that: “A party who offers or uses an audio, audiovisual, or video recording at a hearing or trial shall: (A) ensure that the recording is marked for identification and made part of the record and that an additional copy is provided to the court….”
    • The Committee Note to Rule 2-516 adds: “A party may provide the court with a copy of a recording in a physical media format or in a digital media format using a digital storage platform approved by the State Court Administrator.”
    • The Rule states: “A party who offers or uses a transcript of the recording at a hearing or trial shall ensure that the transcript is made part of the record.”
    • The circuit court can appoint an alternate custodian under Rule 2-516(a)(2): “Unless the court orders otherwise, all exhibits shall remain in the custody of the clerk.  If the court orders that the custodian of an exhibit be someone other than the clerk, the court shall: (A) state the identity of the custodian on the record; (B) instruct the custodian, until relieved of the responsibility by law or by court order, to secure the exhibit until final determination of the action, including all appellate proceedings, and retain the exhibit as required by Rule 16-405 and any statutory retention provisions; and (C) instruct the clerk to make a docket entry identifying the court-ordered custodian of the exhibit.” [emphasis added].
  • In the State of Maryland courts of limited jurisdiction, the District Courts, Rule 3-516(a) states
    • That “[a]ll exhibits marked for identification at hearing or trial, whether or not offered in evidence and, if offered, whether or not admitted, form part of the record.”
    • Subsection (a) adds: “With leave of court, a party may substitute a photograph or copy for any exhibit.”
    • The new Rule also states in Subsection (b): “In an action where an appeal would be tried de novo, exhibits shall be returned to the parties at the conclusion of the proceeding unless the court orders otherwise.”
    • Under Subsection (c), in an action where an appeal would be heard on the record made in the District Court, exhibits shall remain in the custody of the District Court clerk unless the court orders otherwise.” [emphasis added].

Rule 7-109 addresses use of digital media in on-the-record appeal. A Committee Note states: “Exhibits that are audio, audiovisual, or video recordings may be stored and accessed using a digital storage platform approved by the State Court Administrator.  Absent any dispute as to the authenticity or accuracy of the file, the file stored on the approved digital storage platform is considered the original for the purposes of this Rule.”

  • Rule 4-322(c) applies in criminal matters.
    • It generally tracks Rule 2-516 and permits an alternative custodian. It provides for the return of exhibits in the case of a de novo appeal.
    • Subsection (b) adds: “A party who offers or uses computer-generated evidence at any proceeding shall preserve the computer-generated evidence, furnish it to the clerk in a manner suitable for transmittal as a part of the record on appeal, and present the computer-generated evidence to an appellate court if the court so requests.”

Notably, under Rule 20-301(b): “A hyperlink embedded in a submission is not a part of the official record unless it is linked to another document that is a part of the official record.”

DIGITAL MEDIA SUBMITTED WITH MOTIONS

Under Rule 1-322(a), filing of pleadings, papers, and other items, is with the Clerk and “[n]o item may be filed directly by electronic transmission, except…  (6) digital media submitted using a digital storage platform approved by the State Court Administrator.” The Reporter’s Note added: “Proposed new subsection (a)(6) authorizes digital media, as defined by Rule 1-202, to be transmitted using a digital storage platform approved by the State Court Administrator.”

Rule 20-301(a)(4) (“official record”) states that the official record of an action will include all “audio, audiovisual, or video recording exhibits, including digital media,” that are made part of the record under Rule 2-516, 3-516, or 4-322.

The Reporter’s Note added: “Recordings made part of the record pursuant to Rule 2-516, Rule 3-516, or Rule 4-322 may be on physical media, such as a hard drive, disc, or flash drive, but also may be submitted digitally using an approved platform. The current provisions of Rule 20-301 do not incorporate a digital submission that is stored outside of MDEC[1] into the official record in an action.”  [emphasis added].

RECORD IN APPELLATE COURTS

The Committee Note to Rule 8-413(a)(4) (contents of the record on appeal) states that “the original of any audio, audiovisual, or video recording made part of the record pursuant to Rules 2-516, 3-516, or 4-322” is part of the record on appeal.  The Committee Note adds:  “Exhibits that are audio, audiovisual, or video recordings may be stored and accessed using a digital storage platform approved by the State Court Administrator. Absent any dispute as to the authenticity or accuracy of the file, the file stored on the approved digital storage platform is considered the original for the purposes of this Rule.”

It adds that: “A party who offers or uses an audio, audiovisual, or video recording in a format not in common use by the general public is required to provide the recording to the clerk in a medium and format suitable for transmittal as part of the record. See Rule 2-516 (b) and Rule 4-322 (c) pertaining to the use of a recording at a hearing or trial.”

Further, the certificate of the clerk of the lower court shall identify “any digital media included in the record and instructions for access by the appellate court….”

MDEC Rule 16-905(d) states: “If a case record consists of digital media, a copy of the record shall consist of a document containing instructions for accessing the digital media.”

Rule 20-101(f) states: “Electronic filing” does not include digital media submitted and maintained on a digital storage platform approved by the State Court Administrator.

Rule 16-918(a, c) provides for public access to digital media at court kiosks. However, Rule 16-905(e) provides: “A custodian may remove metadata from an electronic document before providing the electronic document to an applicant by using a software program or function or converting the electronic document into a different format.”

This blog was initially posted on  Electronic Discovery Reference Model.

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[1] “MDEC” is the Maryland court’s electronic filing system.  See Rule 20-101(m).  “MDEC” is the acronym for “Maryland Electronic Courts.”  It has two components: 1) electronic filing; and, 2) electronic case management.

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