In today's rapidly evolving legal landscape, the integration of Artificial Intelligence (AI) into investigation and document review processes is transforming the way legal professionals operate. AI technologies promise significant enhancements in efficiency and accuracy, offering cost savings and faster turnaround times.
However, the adoption of AI also requires a nuanced understanding of its capabilities and limitations. This blog explores the strategic use of AI in legal investigations, the importance of differentiating between various AI technologies, and the need for continuous human oversight to ensure reliable and unbiased outcomes. By balancing innovation with caution, legal professionals can harness the full potential of AI while safeguarding the integrity of their work.
Using the Correct Terminology
The term "AI" is often overgeneralized in the eDiscovery space. It is important to differentiate between various technologies such as Machine Learning (e.g., Predictive Coding) and Analytics (e.g., Conceptual Searching, Clustering), which are not the same as Generative AI (GenAI). GenAI is not entirely new but has recently gained traction in the legal industry due to significant improvements in technology.
Large Language Models (LLMs) operate differently from traditional machine learning; they retrieve information based on prompts rather than relying on trained algorithms. Additionally, LLMs often require calls to external models to generate outputs, which introduces new data security considerations that were not historically present. Understanding the capabilities and development of technologies such as LLMs is essential for their gradual adoption in investigation, litigation and document review processes.
Learning New Skills
The strategic use of AI can lead to more thorough and insightful investigations, ultimately benefiting the legal process. Unlike Predictive Coding, which learns from examples coded by human reviewers, GenAI relies on prompts that provide instructions, context, and input data to generate accurate responses.
Attorneys need to develop skills in prompting, which allows them to ask natural language questions about their document sets to identify relevant documents effectively.
Knowing Its Limitations
It is advisable to be cautious when using GenAI as a standalone review feature. Instead, it should be used in conjunction with other established tools like search terms, analytics, and Predictive Coding to ensure a more comprehensive and reliable review process.
AI technologies, including GenAI, can produce hallucinations and may exhibit bias based on their training data. There is also always the challenge of "Not Knowing What You Don’t Know." There may be gaps or inaccuracies in the data or the AI's “understanding” that are not immediately apparent. This can lead to overlooked information or incorrect conclusions because the AI system might not recognize its own limitations or the absence of crucial data.
Confidentiality and Transparency
LLM models vary in transparency regarding their training materials and have not been extensively tested in courts. Some providers do not allow access to the prompts sent to the LLM, raising concerns about transparency. Confidentiality issues may also arise with the preservation and disclosure of prompts.
Summary
- AI can significantly enhance efficiency and accuracy in document review processes.
- Leveraging AI can lead to cost savings and faster turnaround times in investigations.
- AI tools can uncover patterns and insights that might be missed by human reviewers.
- Always approach AI with skepticism and strive to balance what, when, and how to deploy these technologies.
- Iterative feedback and human input are essential to combat and correct bias.
- Be nimble and adaptive to the evolving landscape of AI in investigations.
