Inside Look: Conversations from NACDL’s White Collar Defense Seminar
Inside NACDL’s White Collar Defense Seminar in D.C. - real questions from attorneys on trust, technology, and the future of legal work.
This wasn’t a small mistake - it was a fundamental failure of trust, accuracy, and professional responsibility.
The ruling serves as a clear reminder:
Stop using unverified AI tools to draft legal documents.
In a recent federal case, a lawyer used a general-purpose AI tool to draft legal filings that contained nonexistent case citations.
The judge described the conduct as “more than mere recklessness” and issued sanctions, fines, and professional restrictions.
The incident reflects a growing problem nationwide - attorneys relying on unverified AI for court submissions and damaging client confidence in the process.
Most general AI systems are designed for broad, creative use, not for verified legal accuracy.
They pull from massive internet datasets that mix reliable and unreliable sources.
When prompted for case law, these models can confidently generate citations that don’t exist, because they aren’t connected to verified legal databases.
When AI is used outside of a purpose-built legal platform, errors aren’t rare - they’re inevitable.
The solution isn’t to abandon AI - it’s to use the right kind.
At Matey, we built our platform specifically for legal accuracy, accountability, and transparency - helping professionals work faster while maintaining full confidence in their results.
Here’s how Matey prevents the risks seen in this case:
Yes - if it’s built responsibly.
The difference between a general chatbot and a purpose-built legal AI platform is substantial.
One guesses; the other verifies.
Matey empowers legal teams to go to court with confidence, knowing every line is supported by verified data and fully auditable sources.
This court ruling is a warning to every legal professional using AI:
If you use AI in legal work, you are responsible for verifying what it produces.
AI can strengthen justice and efficiency - but only when it’s built for trust, traceability, and transparency.
That’s exactly why we built Matey.
Because when accuracy determines outcomes, “close enough” isn’t good enough.