Are we chasing the wrong goal with Artificial General Intelligence, and missing the breakthroughs that matter now

On this episode of Digital Disruption, we’re joined by former research director at Google and AI legend, Peter Norvig.

Peter is an American computer scientist and a Distinguished Education Fellow at the Stanford Institute for Human-Centered Artificial Intelligence (HAI). He is also a researcher at Google, where he previously served as Director of Research and led the company’s core search algorithms group. Before joining Google, Norvig headed NASA Ames Research Center’s Computational Sciences Division, where he served as NASA’s senior computer scientist and received the NASA Exceptional Achievement Award in 2001.He is best known as the co-author, alongside Stuart J. Russell, of Artificial Intelligence: A Modern Approach — the world’s most widely used textbook in the field of artificial intelligence.

Peter sits down with Geoff to separate facts from fiction about where AI is really headed. He explains why the hype around Artificial General Intelligence (AGI) misses the point, how today’s models are already “general,” and what truly matters most: making AI safer, more reliable, and human-centered. He discusses the rapid evolution of generative models, the risks of misinformation, AI safety, open-source regulation, and the balance between democratizing AI and containing powerful systems. This conversation explores the impact of AI on jobs, education, cybersecurity, and global inequality, and how organizations can adapt, not by chasing hype, but by aligning AI to business and societal goals. If you want to understand where AI actually stands, beyond the headlines, this is the conversation you need to hear.

In this episode:

00:00 Intro

01:00 How AI evolved since Artificial Intelligence: A Modern Approach

03:00 Is AGI already here? Norvig’s take on general intelligence

06:00 The surprising progress in large language models

08:00 Evolution vs. revolution

10:00 Making AI safer and more reliable

12:00 Lessons from social media and unintended consequences

15:00 The real AI risks: misinformation and misuse

18:00 Inside Stanford’s Human-Centered AI Institute

20:00 Regulation, policy, and the role of government

22:00 Why AI may need an Underwriters Laboratory moment

24:00 Will there be one “winner” in the AI race?

26:00 The open-source dilemma: freedom vs. safety

28:00 Can AI improve cybersecurity more than it harms it?

30:00 “Teach Yourself Programming in 10 Years” in the AI age

33:00 The speed paradox: learning vs. automation

36:00 How AI might (finally) change productivity

38:00 Global economics, China, and leapfrog technologies

42:00 The job market: faster disruption and inequality

45:00 The social safety net and future of full-time work

48:00 Winners, losers, and redistributing value in the AI era

50:00 How CEOs should really approach AI strategy

52:00 Why hiring a “PhD in AI” isn’t the answer

54:00 The democratization of AI for small businesses

56:00 The future of IT and enterprise functions

57:00 Advice for staying relevant as a technologist

59:00 A realistic optimism for AI’s future

Connect with Peter:

LinkedIn: https://www.linkedin.com/in/pnorvig/

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