This forward-looking analysis explores how RAG combines external document retrieval with LLM generation to dramatically reduce hallucinations and enhance factual grounding in legal tasks. Johnston spotlights a November 2024 randomized trial showing that while GPT‑4 speeded up legal work, it didn’t improve accuracy—suggesting RAG’s retrieval layer offers the key breakthrough. This matters for legal professionals because it shows a tangible path to reliable, citation-capable AI tools, built on verifiable sources like statutes and case law. By demonstrating that RAG-equipped systems can elevate LLMs from flashy assistants to trusted research partners, the article invites lawyers and legal tech developers to rethink how they deploy AI in practice.

This digest piece proposes a framework for government‑mandated AI audits, drawing on financial auditing standards to ensure transparency across an AI system’s full lifecycle—from data and model development to deployment. It emphasizes that professional, standards‑based oversight can foster public trust and accountability without stifling innovation, turning audits into drivers of advancement rather than burdensome compliance. Legal professionals will find it essential for understanding what credible, institutionalized AI governance could look like and how regulators may begin enforcing it. By offering actionable reforms and highlighting the role of independent auditors, this article equips lawyers and policymakers with practical guidance to shape and prepare for the next phase of AI regulation.

This press release from the FTC unveils Operation AI Comply, targeting five companies (including DoNotPay and Rytr) for deceptive AI claims—such as fake legal services and AI-driven e-commerce schemes. It highlights that the FTC enforces existing law: misusing AI tools to deceive consumers or generate fake reviews is illegal. This matters for legal professionals because it marks a sharp pivot toward proactive, AI-focused consumer protection, illustrating how liability and enforcement frameworks are evolving in the AI era. With tangible outcomes—fines, cease-and-desist orders, and court actions—this release equips lawyers with critical insights on how to counsel clients offering AI-powered services.

This Perspective by Ben Chester Cheong (Singapore University of Social Sciences & Cambridge) offers a comprehensive legal–ethical review of transparency and accountability challenges in AI systems governing human wellbeing . It structures the discussion into four pillars—technical explainability methods, regulatory frameworks, ethical safeguards, and multi‑stakeholder collaboration—highlighting how each area plays a vital role in ensuring trust and societal resilience. Legal professionals will appreciate its actionable framework that bridges tech, ethics, and governance, making it a timely resource amid emerging regulations like GDPR “right to explanation” and EU AI Act mandates. By offering strategic clarity and policy cohesion, this article equips lawyers, compliance leaders, and policymakers with tools to embed transparency and accountability into AI systems that shape lives—making it a must‑read for anyone advising on responsible AI deployment.

This essay by Margot E. Kaminski and Meg Leta Jones explores how current legal frameworks actively construct AI-generated speech, rather than being passively disrupted by it. It introduces the “legal construction of technology” method—analyzing how laws like the First Amendment, content moderation, risk regulation, and consumer protection actively interpret and shape AI speech. This analysis matters to legal professionals because it reveals that existing institutions and norms already provide structured pathways for meaningful oversight, shifting the conversation from reactive problem-solving to proactive values-based policy design. By demonstrating that law and AI co-evolve through these intentional constructions, this piece empowers lawyers and policymakers to craft more effective, principled governance—prompting deeper engagement with the field.

This article by Graham H. Ryan analyzes how generative AI challenges the legal immunity conferred by Section 230 of the Communications Decency Act—and why that protection may crumble under new judicial scrutiny. Ryan argues that generative AI systems “create or develop content” and thus likely fall outside Section 230’s existing scope, exposing providers to increased liability for design decisions and algorithmic contributions. It matters for legal professionals because emerging case law may redefine liability standards—from co-authoring content to design-based claims—signaling a pivotal shift in AI governance and internet law that practitioners need to monitor closely. By framing generative AI as a catalyst for reevaluating the legal foundations of internet speech, the article urges lawyers to proactively reassess risk strategies and regulatory compliance in this evolving landscape.