The Light and Dark Sides of Auto-GPT with Jason Epstein

Auto-GPT is a new generative artificial intelligence application which autonomously “self-prompts” to engage beyond a human-chatbot discussion.

This takes us into a realm of AI self-prompted actions that do not need additional human inputs. It also potentially puts the “traditional” GPT models on a fast track to further reduce human interaction. The number of use cases as well as the number of legal and ethical questions is inevitable. For that reason, it’s becoming increasingly important for businesses to understand how Auto-GPT technologies use data, the potential for biased results, and how to responsibly leverage these powerful technologies.

Listen to my interview with Jason I. Epstein, Partner at Nelson Mullins Riley & Scarborough as we explore this emerging field. Jason is the co-head of the firm’s technology and procurement industry group which provides legal services to global buyers and sellers of technology in industries that include FinTech, HealthIT,  and manufacturing. An experienced business and technology negotiator, Jason has dealt with a variety of matters, e.g., the metaverse, technology transfer, privacy, cryptocurrency, IoT, open-source code, and more. Jason received his JD from the University of Tennessee College of Law. He also teaches “Law of Cyberspace” as an adjunct professor at Vanderbilt University Law School. 

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This podcast is the audio companion to the Journal on Emerging Issues in Litigation. The Journal is a collaborative project between HB Litigation Conferences and the Fastcaselegal research family, which includes Full Court Press, Law Street Media, and Docket Alarm. The podcast itself is a joint effort between HB and our friends at Law Street Media. If you have comments or wish to participate in one our projects please drop me a note at

Tom Hagy
Litigation Enthusiast and
Host of the Emerging Litigation Podcast
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