Criminal Law Library Blog
Artificial intelligence is now woven into the daily fabric of legal work. From case law research to contract analysis and compliance monitoring, AI systems are accelerating tasks that once required hours of manual review. But as these tools become more capable, the legal profession faces a central challenge: How can lawyers trust AI in high‑stakes environments where accuracy, transparency, and defensibility are non‑negotiable?
Two concepts have emerged as foundational to answering that question: interpretability and retrieval-augmented generation (RAG). While distinct, they work together to create AI systems that are transparent, grounded in evidence, and aligned with professional legal standards. Although both have existed for some time, their integration into legal research remains in its infancy, and there is much to learn. This post explores how these systems are reshaping AI legal research based on a review of current industry sources.