NYC Bar Provides Roadmap for Navigating AI Privilege Issues

Here is my recent Daily Record column. My past Daily Record articles can be accessed here.

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NYC Bar Provides Roadmap for Navigating AI Privilege Issues

I’ve spent a lot of time over the past few months tracking cases that address the applicability of the work product doctrine and attorney-client privilege to generative artificial intelligence (GenAI) usage. Rulings have varied across state and federal courts, with the conclusions often determined by the status of the person using AI. Some courts treat pro se litigants differently from represented parties, and others focus more on the expectations surrounding the AI use.

There is not yet a consensus or clear-cut rule, and the approaches for analyzing the issues involved run the gamut. Courts vary in their understanding and interpretation of the technology, its limitations, and its risks. As a result, this unsettled and emerging area of law feels an awful lot like the wild, wild west, something that is not entirely uncommon during the early adoption stages of a new technology. Applying existing precedent to untested technology can be challenging—which is exactly why the New York City Bar Association’s “Presidential Task Force Report on Artificial Intelligence and Digital Technologies" so timely.

Released in June, it is incredibly thorough, focusing on how large language models (LLMs) and their privacy policies impact confidential and privileged information. It covers the evolution of the Third-Party Doctrine in the context of generative AI and provides practical guidance for lawyers on the steps to take to protect the attorney-client privilege and work product.

The second section on how LLMs work is incredibly informative and well-researched. Even though I like to think I have a good understanding of the inner workings of LLMs, there were a few concepts discussed that were new to me. Definitely don’t bypass this portion of the report.

The report also provides an overview of current caselaw, describing how the courts “have split on whether GenAI is a tool or a substitute-human for third-party disclosure purposes.” The authors caution against treating AI differently from the technology that preceded it: “While agentic AI’s methodology is more complex than entering text into a word-processing application, software’s ability to imitate more complex interactions and functions does not transform the tool into something more.“ 

According to the authors, when courts consider whether the third-party waiver rule applies to risks created when confidential information is shared with others, the focus should be on “whether the GenAI interaction actually created those risks.” 

When “a waiver theory is framed in terms of ‘consent’ via privacy notices or terms of service, focused briefing may help the court determine whether that consent was meaningfully informed and voluntary or instead resembles the constrained consent analysis courts have confronted in other modern third‑party settings.”

Similarly, the importance of consistency in analysis was emphasized. When considering how technology use impacts privilege, the authors recommend that  judges avoid treating an AI provider’s generalized terms “as dispositive of confidentiality or as a basis for concluding that a provider does not have a substantial interest in privacy in a way that would destabilize settled practice with cloud and communications services.”

Another important section is Part V, which provides practical guidance, including very helpful frameworks for addressing privilege disputes involving GenAI tools, both for lawyers and the judiciary. 

Notably, the authors wisely advise attorneys to be proactive and head off any potential privilege waivers by counseling clients about GenAI use at the start of a case. 

They recommend that: 1) “(e)ngagement letters and client onboarding should address GenAI use explicitly,” 2) “clients should be advised that consumer GenAI tools are not a substitute for attorney-client communications,” and 3) clients should be cautioned “against using the ‘share’ or ‘export’ features now common in consumer GenAI tools for any conversation touching privileged matter: such features can create publicly accessible URLs whose downstream copies in third-party archives.”

For New York lawyers, this 26-page document is a must-read. And even if you practice elsewhere, don’t overlook it. It offers a wealth of information and analysis on the evolving issue of whether—and when—AI interactions are privileged. GenAI use is exploding, and its impact on your law practice cannot be avoided. Understanding GenAI is essential and part of your competency obligations. This report offers an invaluable roadmap to help you get up to speed, ensuring that your firm is well-equipped to proactively protect its clients and safeguard their interests in an increasingly AI-first landscape.

Nicole Black is a Rochester, New York attorney, author, journalist, and Principal Legal Insight Strategist at 8am, the team behind MyCase, LawPay, CasePeer, and DocketWise.She is the nationally-recognized author of "Cloud Computing for Lawyers" (2012) and co-authors "Social Media for Lawyers: The Next Frontier" (2010), both published by the American Bar Association. She also co-authors "Criminal Law in New York," a Thomson Reuters treatise. She writes regular columns for Above the Law, ABA Journal, and The Daily Record, has authored hundreds of articles for other publications, and regularly speaks at conferences regarding the intersection of law and emerging technologies. She is an ABA Legal Rebel, and is listed on the Fastcase 50 and ABA LTRC Women in Legal Tech. She can be contacted at niki.black@mycase.com.