The traditional privilege logging process has long been synonymous with burden, inefficiency, and resource drain. It is a complex and time-consuming undertaking that can strain even the most seasoned legal professionals.
For at least a decade, litigation teams have leveraged technology such as machine learning to streamline and improve the e-discovery process. Predictive coding tools like TAR (technology-assisted review) and CAL (continuous active learning) have significantly streamlined the identification of relevant documents. The advent of generative AI represents another significant leap forward, offering litigators an entirely new realm of possibilities to boost efficiency and effectiveness. Given their prior experience with machine learning technology, e-discovery teams and technology-forward litigators are well-positioned to adopt generative AI tools, remembering that these tools are not silver bullets, but rather applications that can handle appropriate parts of a workflow very well.
In fact, privilege logging is a prime area where litigation teams are leveraging or considering AI/generative AI, with 45% of law firms and 50% of legal departments already using or planning to use GenAI for this task, according to a recent UnitedLex survey of more than 200 litigation professionals. As legal departments continue to modernize their operations, they are weighing the ethical considerations and potential risks around the use of genAI.
The Sedona Conference Commentary: A Guiding Light
Although parties must now contend with large volumes of ESI (electronically stored information) in modern litigation, the formal rules around claiming privilege have not changed, creating challenges with providing narratives on a document-by-document basis that satisfy them. With the privilege logging process anecdotally costing around $1 million per matter in some large cases, the Sedona Conference Working Group 1 in May 2024 offered a beacon of hope in this challenging landscape when it introduced its Commentary on Privilege Logs. This Commentary presents the latest thinking on strategies and tools for both responding and requesting parties to alleviate the significant burdens and navigate the inherent complexities of privilege logging.
The Sedona Conference Commentary is an essential resource that redefines the privilege logging process, addressing its inherent challenges with practical solutions. By offering guidance on the scope of privilege logs and advocating for increased collaboration and transparency, this document equips legal practitioners with actionable insights to improve the efficiency and effectiveness of privilege logging.
For example, the Commentary provides templates for privilege logs that contend with different types of metadata, cross-platform communications, and other complex data challenges. The Commentary will no doubt serve as an indispensable tool for counsel navigating these new frontiers in e-discovery.
Tools and Strategies to Mitigate the Burden
Before addressing AI and generative AI in privilege logging, it is important to keep in mind the array of other technologies that have already revolutionized e-discovery practice.
- Technology-Assisted Review (TAR): TAR utilizes advanced algorithms and machine learning to automate the review and categorization of documents, significantly reducing the time and effort required for privilege logging.
- Predictive Coding: This technology leverages machine learning algorithms to predict which documents are likely to be privileged, enabling legal teams to prioritize their review efforts.
- Collaboration and Communication: Fostering open communication and collaboration between responding and requesting parties can facilitate the identification and resolution of privilege issues early on, minimizing disputes and delays.
- Sampling and Statistical Analysis: Employing sampling techniques and statistical analysis can provide a reliable estimate of the overall prevalence of privileged documents, reducing the need for a comprehensive review.
Navigating Competing Interests and Resolving Disputes
In addition to the Sedona Commentary’s recent guidance, established principles of e-discovery practice can help head off conflicts and help efficiently resolve disputes when they arise.
- Early Case Assessment: Conducting an early case assessment can help identify potential privilege issues and facilitate the development of a mutually agreeable privilege log protocol.
- Negotiation and Compromise: Engaging in good-faith negotiations and being open to compromise can often lead to mutually satisfactory solutions, avoiding costly and time-consuming disputes.
- Judicial Intervention: In exceptional cases, seeking early judicial intervention may be necessary to resolve intractable privilege disputes. However, this should be a last resort, as it can be costly and time-consuming.
AI in Privilege Logging: Benefits and Risks
Artificial Intelligence (AI) has the potential to revolutionize privilege logging by further automating and streamlining the process. AI in privilege logging offers a multitude of benefits, including cost reduction, enhanced efficiency, and increased accuracy.
Some of the key privilege logging tasks that AI can accomplish are:
- Custodian identification (recognizing lawyer by first name)
- Generating subject matter summary
- Identifying exclusions
However, it is crucial to acknowledge the associated risks and recognize and address the ethical considerations surrounding AI, especially in the context of ABA Formal Opinion 512 on generative AI tools.
ABA Formal Opinion 512 provides guidance on the ethical use of Generative AI tools in the legal profession. When utilizing AI in privilege logging, it is imperative to adhere to these ethical principles.
- Competence: Legal professionals must possess the necessary knowledge and skills to effectively use AI tools in privilege logging or align with and be advised by a professional who does.
- Diligence: AI should be used as a tool to enhance, not replace, human judgment. Legal professionals must exercise due diligence in supervising and reviewing AI-generated results.
- Confidentiality: Protecting client confidentiality remains paramount. Adequate safeguards must be in place to prevent unauthorized access or disclosure of sensitive information.
In addition, it is important for counsel to acknowledge that AI is not a “silver bullet” to solve all issues with privilege logging. This will remain a complex process, and AI tools must exist within workflows that are intelligently designed and diligently human-checked.
Yet this is an exciting time, with the traditional privilege logging process ripe for transformation by AI. The Sedona Conference Commentary provides a valuable roadmap for navigating the complexities of privilege logging and embracing innovative solutions. By leveraging tools and strategies such as TAR, predictive coding, collaboration, and AI, legal practitioners can streamline the process, reduce costs, and achieve more efficient and effective outcomes.
As AI continues to evolve, it holds immense promise for further revolutionizing privilege logging. However, it is crucial to proceed with caution, ensuring that AI is used ethically and responsibly, always prioritizing client confidentiality and the integrity of the legal process.
Aaron Crews is chief innovation officer at UnitedLex. Before joining UnitedLex, Aaron held two senior-level roles at Littler Mendelson, first as a litigating shareholder in the firm’s e-discovery group, and then as the firm’s Chief Data Analytics Officer. He earned his BA from the University of California, Davis and his JD from the University of San Francisco School of Law.
