Generative AI & Ethics in Legal Practice CLE
This course, Generative AI & Ethics in Legal Practice, presented by John Goodhue of Goodhue, Coleman & Owens, P.C. and recorded on December 10, 2025, provides a practical and comprehensive overview of how modern generative AI intersects with lawyers’ ethical responsibilities. The program begins with ABA Formal Opinion 512 and explores its guidance on competence, confidentiality, communication, supervision, meritorious claims and candor to the tribunal, and reasonable fees, emphasizing both what the opinion clarifies and what remains unchanged in existing ethical duties. From there, the course introduces the technical foundations necessary to understand generative AI, including the distinctions between traditional AI and GPT models, the mechanics of pre-training and inference, the role of tokens and neural networks, and the importance of transformer architectures and attention mechanisms. Building on this foundation, the presentation examines both the strengths and limitations of GPT models, including their capabilities, the risks associated with them, and the dynamics of hallucinations. It then addresses methods for mitigating these risks through retrieval-augmented generation (RAG), APIs and structured tools, and redesigned legal workflows, including the challenges of AI-driven “slop.” Real-world consequences are illustrated through a hallucination case example and the Iowa Court of Appeals decision in In the Interest of R.A., followed by additional discussion of the inherent “weirdness” of hallucinations. The course concludes with a detailed case study—EligibilityEdge—demonstrating how domain-specific, retrieval-grounded AI systems can enhance accuracy and reduce risk in practice.
Free
