A2JC Executive Director Reena Shah Joins Podcast to Discuss AI and Access to Justice
Maryland has about 40,000 lawyers. Roughly half a percent of them work in civil legal aid. Add more lawyers, and you still hit a ceiling, because every lawyer can only serve so many people. Reena Shah, Executive Director of the Maryland Access to Justice Commission, joined Ron Drescher and Heather Gardner on their podcast AI Tools for Practicing Lawyers to ask what happens when technology breaks through that ceiling, and what happens when the general-purpose chatbots break through it first. What if AI’s biggest contribution to law isn’t making lawyers faster, but reaching the people who never had a lawyer at all?
In the episode, they discuss:
- The civil justice gap in Maryland: no right to counsel in civil cases, 40% of households unable to cover basic needs, and legal aid organizations meeting roughly 20% of demand
- Maryland’s AI and Access to Justice Summit, one of the first state commission events of its kind, and why it was run as a hands-on workshop instead of a lecture
- What a pre-summit survey of 187 legal aid staff revealed: few AI policies, few enterprise tools, and no clear organizational stance on staff use
- Why Maryland Legal Aid’s Vicki Schultz says policy comes first, and why that policy has to start with the organization’s values
- Self-represented litigants walking into Court Help Centers with 20-page AI-generated pleadings, and refusing to believe the lawyers who tell them it’s wrong
- The Innovations in Tiered Legal Services Task Force and its push for a UPL waiver to test safe, closed AI tools in low-risk areas of law
- Drescher’s and Gardner’s disagreement: teach pro se litigants to use AI responsibly, or hand them a vetted tool? And is the teaching itself UPL?
- The Nippon Life lawsuit against OpenAI, and why Shah argues the big AI companies crossed the UPL line without ever asking permission
- Users vs. builders for legal aid: Maryland Legal Aid’s home-grown MLA GPT, rent ledger reviewer, and brief creator versus off-the-shelf tools like NotebookLM
- A TurboTax-style expungement tool as a model for scaling high-volume legal help
They also talk about:
- Anthropic’s Claude for Legal launch and the connectors and skills it included for pro bono and legal aid organizations
- Whether AI companies should give legal aid organizations pro bono or reduced-cost access, and who is actually asking them
- Why AI is a prediction model, not a search engine, and how that distinction shapes training
- The People’s Law Library and the work of making legal websites accurate enough for AI tools to pull from
- Practice Signals: a Reddit lawyer asks where the access-to-justice gaps are, and Ron adds a fourth question about what AI can fill
- The AI Doc: Or How I Became an Apocaloptimist, and a preview of the show’s 50th episode
Key Takeaways
Shah’s argument is about math, not efficiency. Every lawyer has an upper limit. Technology is the only thing on the table that scales past it, but only if it’s built safely and vetted before anyone relies on it. Meanwhile, the general-purpose chatbots are already giving legal advice to people who can’t tell a good answer from a confident one. Availability is not authority. The pro se litigant arguing with the Court Help Center lawyer hasn’t learned that yet.
For users, the lawyers running off-the-shelf tools, this episode is a warning about who is sitting across the table: more and more often, it’s someone holding an AI-drafted answer they trust more than you. For builders, Maryland Legal Aid shows what a small team with real subject-matter expertise can do at low cost: narrow tools aimed at narrow, repetitive problems. Solo and small firm lawyers live with the same constraint legal aid does. There’s more demand than there are hours.
You can listen to or watch the episode here: Spotify • Apple Podcasts • YouTube