
Sign up to save your podcasts
Or


In this episode of 2030 Vision: AI and the Future of Law, hosts Bridget McCormack and Jen Leonard unpack groundbreaking insights from a JAMA study that compares the diagnostic capabilities of ChatGPT with human doctors. Drawing compelling parallels to the legal profession, they explore how generative AI could reshape legal research, improve efficiency, and challenge long-standing notions of professional judgment and subjectivity.
Through interdisciplinary insights, Jen and Bridget highlight the parallels and contrasts between medicine and law—such as the objective nature of medical diagnostics versus the subjective complexities of legal outcomes—and emphasize the urgent need for innovation, ethical considerations, and transparency in both fields.
The conversation delves into personal AI aha moments, clarifies essential terms like zero-shot and few-shot prompting, and considers how AI adoption in medicine might provide valuable lessons for the legal field. They discuss overcoming algorithmic aversion, increasing transparency, and rethinking professional roles as technology advances.
Key Takeaways
Keywords
AI, Law, Medical Diagnosis, ChatGPT, Legal Education, Technology, Generative AI, Legal Profession, AI Terminology, Future of Law, medicine, technology, legal innovation, client expectations, legal research, subjectivity, ethics, transparency
2030 Vision: AI and the Future of Law is your essential podcast for understanding how artificial intelligence is revolutionizing the legal industry. Hosted by Bridget McCormack and Jen Leonard, each episode delves into cutting-edge technologies, trends, and strategies, providing invaluable insights for legal professionals, tech enthusiasts, and anyone curious about the future of law. Join us as we navigate the evolving landscape of AI, empowering the legal community to thrive in an era of unprecedented innovation.
Produced by Aaron Tran for the American Arbitration Association
Hosted on Acast. See acast.com/privacy for more information.
By Practising Law Institute5
88 ratings
In this episode of 2030 Vision: AI and the Future of Law, hosts Bridget McCormack and Jen Leonard unpack groundbreaking insights from a JAMA study that compares the diagnostic capabilities of ChatGPT with human doctors. Drawing compelling parallels to the legal profession, they explore how generative AI could reshape legal research, improve efficiency, and challenge long-standing notions of professional judgment and subjectivity.
Through interdisciplinary insights, Jen and Bridget highlight the parallels and contrasts between medicine and law—such as the objective nature of medical diagnostics versus the subjective complexities of legal outcomes—and emphasize the urgent need for innovation, ethical considerations, and transparency in both fields.
The conversation delves into personal AI aha moments, clarifies essential terms like zero-shot and few-shot prompting, and considers how AI adoption in medicine might provide valuable lessons for the legal field. They discuss overcoming algorithmic aversion, increasing transparency, and rethinking professional roles as technology advances.
Key Takeaways
Keywords
AI, Law, Medical Diagnosis, ChatGPT, Legal Education, Technology, Generative AI, Legal Profession, AI Terminology, Future of Law, medicine, technology, legal innovation, client expectations, legal research, subjectivity, ethics, transparency
2030 Vision: AI and the Future of Law is your essential podcast for understanding how artificial intelligence is revolutionizing the legal industry. Hosted by Bridget McCormack and Jen Leonard, each episode delves into cutting-edge technologies, trends, and strategies, providing invaluable insights for legal professionals, tech enthusiasts, and anyone curious about the future of law. Join us as we navigate the evolving landscape of AI, empowering the legal community to thrive in an era of unprecedented innovation.
Produced by Aaron Tran for the American Arbitration Association
Hosted on Acast. See acast.com/privacy for more information.

4,174 Listeners

1,708 Listeners

377 Listeners

2,453 Listeners

1,084 Listeners

112,501 Listeners

227 Listeners

7,230 Listeners

492 Listeners

5,528 Listeners

15,984 Listeners

444 Listeners

48 Listeners

4 Listeners

53 Listeners