Tony Thai and Ashley Carlisle of HyperDraft, return to The Geek in Review podcast to provide an update on the state of generative AI in the legal industry. It has been 6 months since their last appearance, when the AI Hype Cycle was on the rise. We wanted to get them back on the show to see where we are on that hype cycle at the moment.
While hype around tools like ChatGPT has started to level off, Tony and Ashley note there is still a lot of misinformation and unrealistic expectations about what this technology can currently achieve. Over the past few months, HyperDraft has received an influx of requests from law firms and legal departments for education and consulting on how to practically apply AI like large language models. Many organizations feel pressure from management to "do something" with AI, but lack a clear understanding of the concrete problems they aim to solve. This results in a solution in search of a problem situation.
Tony and Ashley provide several key lessons learned regarding limitations of generative AI. It is not a magic bullet or panacea – you still have to put in the work to standardize processes before automating them. The technology excels at research, data extraction and summarization, but struggles to create final, high-quality legal work product. If the issue being addressed is about standardizing processes or topics, then having the ability to create 50 different ways to answer the issue doesn't create standards, it creates chaos.
Current useful applications center on legal research, brainstorming, administrative tasks – not mission-critical legal analysis. The hype around generative AI could dampen innovation in process automation using robotic process automation and expert systems. Casetext's acquisition by Thomson Reuters illustrates the present-day limitations of large language models trained primarily on case law.
Looking to the near future, Tony and Ashley predict the AI hype cycle will continue to fizzle out as focus shifts to education and literacy around all forms of AI. More legal tech products will likely combine specialized AI tools with large language models. And law firms may finally move towards flat rate billing models in order to meet client expectations around efficiency gains from AI.
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Music: Jerry David DeCicca
Transcript
An Overview of the 2022 Partner Compensation Survey with Law360's Craig Savitzky and MLA's Jeffrey Lowe (TGIR Ep. 178)
It's Not Legal Technology That's the Problem… It's the Culture - ALM's Tomek Jankowski (TGIR Ep. 177)
Preparing for the Legal Team of the Future - Adam Curphey (TGIR Ep. 176)
What Does a Post-Pandemic Conference Look Like? Martha Breil on ILTACon (TGIR Ep.175)
A Data Diva and Two Geeks Talk Data Privacy - Debbie Reynolds
Intentional Leadership is about Owning Your Purpose - HBR's Axelle Flemming
The Future of Legal Innovation Will Be Built In By Design - Olga Mack
Teaching (and Pressuring) Law Professors to Teach Technology - Katie Brown
11 Steps Law Firms Can Take to Stop "Women Leaving Law" - Laura Leopard
Increased Revenue, Profits, and Efficiencies through "Smarter Collaboration" - Dr. Heidi Gardner
Aliza Shatzman - Turning a Horrible Judicial Clerkship Experience into the Legal Accountability Project
HyperDraft's Tony Thai and Sean Greaney - The Compatibility of BigLaw and Innovative Lawyers
Leading with Love as a Business Strategy with Jeff Ma and Frank Danna
Engineering Serendipity with The Houston Ion's Joey Sanchez
Diane Rodriguez and Beth Adelman on AALL's Preparation for an In-Person Denver Conference
Peter Baumann: There is So Much Value In Your Data… Once You Control the Risks
Law360's Kerry Benn on 2022 Summer Associate Preferences, Challenges, and Options
Colin McCarthy of Legal Operators on Building a LegalOps Community
Sonja Ebron and Ed Walters Collaborate on Courtroom5 and Fastcase to Help Pro Se Litigants Access Justice
After-Hours with NRF's Zack Barnes
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