In this episode, we talk about RAG — Retrieval-Augmented Generation — in the legal domain. What it is, how it works, and, most importantly, what risks it introduces for the legal professional.
RAG allows a model to work with documents provided by the user rather than relying solely on its training data. The idea is powerful, but the process conceals concrete pitfalls: retrieval based on linguistic rather than legal similarity, document fragmentation that breaks argumentative structure, outdated sources retrieved without validity checks, opacity in how fragments are used, and implications for professional secrecy.
Four practical safeguards: verify the sources, check the segmentation, choose the infrastructure carefully, and document every use.
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