Join Ted as he engages with Damien Riehl to explore the transformative intersection of AI and the legal profession. This conversation unpacks the evolving role of large language models in legal reasoning, how they reshape traditional tasks, and the philosophical implications of trusting AI outputs. Whether you're curious about the limits of AI's "reasoning" or its practical benefits for attorneys, this episode offers fresh perspectives and insights you won't want to miss.
In this episode, Damien shares insights on how to:
- Assess the reasoning capabilities of large language models in legal contexts
- Leverage generative AI to enhance legal document drafting and research
- Interpret the limitations of AI outputs in subjective fields like law
- Test the reliability and objectivity of AI systems in complex decision-making
- Navigate ethical considerations in adopting AI-driven tools in legal practice
Key takeaways:
- AI’s reasoning in law aligns with its backward-looking nature, as legal tasks often rely on precedent and existing data, making large language models effective for linking facts to statutes and regulations.
- The “anesthesia test” emphasizes evaluating AI by its practical outputs, as effectiveness matters more than understanding its internal workings.
- While large language models excel at connecting legal concepts, they struggle with objective tasks like math, reflecting their contextual strengths.
- Studies like Stanford’s highlight AI’s limitations, but the legal industry should focus on practical applications for everyday workflows rather than edge cases.
About the guest, Damien Riehl:
Damien Riehl is a lawyer and technologist with experience in complex litigation, digital forensics, and software development. A lawyer since 2002 and coder since 1985, Damien clerked for the chief judges of state and federal courts, practiced in complex litigation for over a decade, has led teams of cybersecurity and world-spanning digital forensics investigations, and has built AI-backed legal software.
At vLex Group — which includes Fastcase, NextChapter, and Docket Alarm — Damien helps lead the design, development, and expansion of various products, integrating AI-backed technologies (e.g., GPT) into a billion-document dataset from 100+ countries, all to improve legal workflows.
“How much of the law is looking backward—that is, looking to precedent? You're always looking to statutes; you're always looking to something that is in the data set. So, if it is in the data set, really, all of our reasoning that is legal is backward-looking, not forward-looking.” – Damien Riehl
Connect with Damien Riehl:
Website: https://vlex.com/
LinkedIn: https://www.linkedin.com/in/damienriehl/
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