Integrating Innovation with Methodological Integrity
Generative AI (AI) is creating exciting opportunities in the realm of complex litigation and expert witness preparation. The technology offers meaningful value that ultimately allows experts to focus their time on high-level analysis and critical judgment. The central focus is not whether to use AI, but how to harness its power responsibly to meet the high standards required for high-stakes litigation.
Bridging the AI-Litigation Gap
AI offers litigation teams an unprecedented ability to accelerate preliminary data-heavy tasks so that experts and their teams can dedicate more time to substantive, high-value analysis and critical reasoning. Yet there is an understandable gap between what judges are comfortable accepting and the current state of technology. While the technology is powerful, the natural caution currently observed in the courts reflects the necessary high bar for evidence and methodology.
But think back to how courts have overcome initial skepticism to technologies in the past. Consider that PowerPoint, now ubiquitous in courtrooms, was once discouraged or outright forbidden.
This current gap between AI’s proven usefulness and professional uncertainty will inevitably shrink over time. However, the key to bridging this gap is not avoiding the technology, but reinforcing rigorous auditing of all outputs. AI becomes a challenge only when it is used naively to generate content without carefully checking and auditing the work. Experts will do what they have always been expected to do: maintain ultimate control over the opinions they form.
Ensuring Admissibility: Discipline, Auditing, and Disclosure
The actual risks of mistakes or “hallucinations” in expert reports are often overblown. This is not because AI is perfect, but because experienced experts already apply the highest standards of auditing and monitoring to their work. AI in the hands of a proficient expert is a tool for synthesis, not a substitute for judgment.
Courts view AI through the lens of admissibility, which hinges on the expert’s ability to clearly and independently connect the bases of their opinions to identifiable, verifiable sources. This means the fundamental responsibilities of the expert are unchanged: to maintain ultimate control over the formation of opinions, ensure verifiable traceability for analytical bases, and be thoughtful about the standards of disclosure.
This article was developed based on discussion from “Unlocking GenAI’s Potential in Expert Witness Work: Balancing Innovation, Risk, and Admissibility” at Legal AI: New York.