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
Unicourt's Josh Blandi on Improving Access to Federal, State, and Local Court Data
Molly Huie on Bloomberg Law's New DEI Framework
Jennifer Leonard of Penn Law's Future of the Profession Initiative
Nicole Bradick and Ryan McClead on the Launch of Map Engine and Life as a Startup Founder
Pablo Arredondo on CaseText's New WeSearch Tool and How the Neural Net Is Making Its Way Into Legal Information
Bob Taylor, Valerie Dickerson, and Mark Ross on Deloitte Legal Business Services
Dan Packel on the Rise of Distributed Law Firms
Adam Tsao and The Creativity Playbook for Lawyers
Kate Tompkins on Being a Practice Group Leader But Not a Lawyer
What's Next for Jeroen Plink?
Lex Machina's Karl Harris on the Past, Present, and Future of Legal Analytics
Sophia George and Chevazz Brown: Finding Diverse Lawyers via DiversePro
Geoff Zodda on Legal Industry Employment Trends in a Post-COVID World
Rachel Travers on the New Law360 Pulse
Brightflag's Alex Kelly on Using Data and Analytics to Make Better Legal Spend Decisions
AI for Lawyers with Noah Waisberg and Dr. Alexander Hudek
Nicole Morris on Emory Law Schools TI:GER Innovation Conference
How Mid-Level Associates Can Thrive at Law Firms - with Jennifer Bluestein
Jennifer Bluestein on Stepping It Up: A Guide for Mid-Level Law Firm Associates
The Who, What, and Why of #LegalTech with Kristin Hodgins and Jason Wilson
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