EP40 - AI – How did we get here and where are we going?

AI is becoming ubiquitous in our lives. It shapes how we work, play, interact, create, and even manage our health—and this is only the beginning. To understand where we are and where we might go, we first need to understand how we got here. By tracing the evolving nature of machine intelligence, we can appreciate how today’s AI differs from its past and how it is likely to evolve. With that in mind, we can begin to ask the big questions: When should we trust AI over human judgment? How should we govern its development? How will it change what it means to be human? And what roles will humans play in the future of work?To help us through this journey, I’m delighted to welcome back to TRIUM Connects Professor Vasant Dhar, the Robert A. Miller Professor at NYU’s Stern School of Business and Professor of Data Science at NYU. Vasant is one of the world’s leading thinkers on the impact of AI on society. He was present at the birth of AI and has been involved in every step of its evolution—both as an entrepreneur and as a scholar. He also hosts the acclaimed podcast Brave New World, which explores how machines are transforming humanity in the post-COVID era.In this episode, we discuss his newest book, Thinking With Machines: The Brave New World of AI. It’s a remarkable hybrid: part autobiography, tracing how his professional life has intertwined with the development of AI; part user’s guide, offering a lucid framework for deciding when to trust machines over human control; and part deep dive into the philosophical and policy implications of creating an alien intelligence.It was a real pleasure to welcome Vasant back onto the show. I learned a lot during our conversation, and I hope you will enjoy it as much as I did.CitationsDawid A, LeCun Y. Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence. arXiv. June 5, 2023.Dennett DC. Intentional systems. J Philos. 1971;68(4):87-106.Dhar V. Thinking With Machines: The Brave New World of AI. Galloway S, foreword. Hoboken, NJ: Wiley; 2025.Frank, R. H., & Cook, P. J. The winner-take-all society: Why the few at the top get so much more than the rest of us. Penguin Books; 1995.Ganguli D, Askell A, Henighan T, et al. Alignment faking in large language models. arXiv. December 20, 2024.Harari YN. Nexus: A Brief History of Information Networks from the Stone Age to AI. New York, NY: Random House; 2024.Kauffmann J, Dippel J, Ruff L, et al. Explainable AI reveals Clever Hans effects in unsupervised learning models. Nat Mach Intell. 2025;7:1–10.Pearl J, Mackenzie D. The Book of Why: The New Science of Cause and Effect. New York, NY: Basic Books; 2018.Pfungst O. Clever Hans (The Horse of Mr. Von Osten): A Contribution to Experimental Animal and Human Psychology. Rahn H, trans. New York: Henry Holt; 1911.Popper KR. The Logic of Scientific Discovery. London, UK: Hutchinson; 1959Suleyman M, Bhaskar M. The Coming Wave: Technology, Power, and the Twenty-First Century’s Greatest Dilemma. New York, NY: Crown; 2023.Yudkowsky E, Soares N. If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All. New York, NY: Little, Brown and Company; 2025. Hosted on Acast. See acast.com/privacy for more information.