Podcast #5 Intersecting Generative AI and Law with Mark Lemley, Stanford Professor of Law and Technology

🌐 How does generative AI shape the future of law? 🌐 In our latest chat with Mark Lemley, one of the most cited legal scholars globally, we explore the complex world of Gen AI and copyright.

Mark Lemley is the William H. Newcomb Professor of Law at Stanford Law School and Director of the Stanford Program in Law, Science, and Technology. Mark Lemley is a distinguished authority in intellectual property, antitrust, and related areas of law.

Mark Lemley's credentials speak for themselves. He has shaped legal thought in multiple domains as a prolific author of 11 books and 218 articles. Among his accolades, he has nine of the most-cited law review articles of the last 20 years and was recognized as the third most-cited legal scholar globally from 2016 to 2020. His extensive experience includes active participation in over three dozen Supreme Court cases and a diverse client base, ranging from tech giants like Genentech to unique groups like Dykes on Bikes and generative AI companies.

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We kick off with a fundamental question: What constitutes copyright infringement?

Mark explains that the basics of copyright revolve around the ease of obtaining protection and the critical act of copying. He then addresses how Generative AI presents novel legal conundrums, particularly regarding the legality of training on vast datasets of copyrighted works. Lemley elucidates that these datasets are essential for teaching AI systems about language and concepts, often involving temporary copying.

He parallels historical cases like Google Book Search and video game software reverse engineering, arguing that training datasets for AI could similarly be considered fair use due to their transformative purposes. *Mark Lemley's insights offer a nuanced perspective on the interplay between technology and law, advocating for thoughtful regulation and collaboration to harness AI's transformative potential while respecting creators' rights.

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