We Need to Stop Panicking About AI (with Andrew McAfee and Nils Gilman)

**Dawn Nakagawa** (0:00)
Hi, I'm Dawn Nakagawa, the host of Futurology. In this interview, Nils Gilman talks with Andrew McAfee.
Andrew was a research scientist, economist, and author who studies technology and its impact on markets and society. At the Berggruen Institute, we consider ourselves dystopian-aware techno-optimists. And what that means is essentially we do understand that there's a great and wonderful future available to humanity with the tools that AI gives us, the discoveries that it will make. However, there are a lot of downside risks that need to be actively managed. Like with any technology, you won't find much dystopian awareness in this conversation. Andrew clearly is a techno-optimist. He believes that technology is leading us to a brilliant future and already has had monumental positive impact on society. And now, Andrew McAfee and Nils Gilman on Futurology.

**Nils Gilman** (1:01)
Andy McAfee, welcome to the Futurology Podcast.

**Andrew McAfee** (1:04)
Nils, it is good to be here.

**Nils Gilman** (1:05)
So, just for the audience to know, we've been friends for a long time. So I know a little bit about your backstory, but maybe we're going to talk a lot about AI, technology, innovation and the innovation economy, which is the stuff that you work on as a research scientist at MIT and now as a founder of a company, Warkeelix.
And so what I'd like to start with is just, how did you get into this? I mean, you've been doing nerdy stuff since you were a little kid. And you've been interested in AI, particularly since before it got super popular in the last few years. So tell me your story about how you got into all of this.

**Andrew McAfee** (1:38)
It's kind of like asking a fish how it got started swimming, right? They're like, nerds do nerdy stuff. My guess is that you're not a huge exception to that rule.
I grew up in a small town in Indiana, and I guess my nerdiness was looking for the thing to anchor on. And the one thing that I knew from a really early age, I grew up with my nose in a book. And then, do you remember Omni magazine? Does that ring a bell?

**Nils Gilman** (2:03)
Yeah, the 70s.

**Andrew McAfee** (2:04)
Thank you. I think Omni came out. I think the first issue was in 1977
And for those of us who are not as old as you and me, Omni was the Wired of its day. And I guess Wired is way less cool than it used to be. But in the 90s, Wired was the thing.

**Nils Gilman** (2:20)
Wired is back, Ben.

**Andrew McAfee** (2:21)
Is Wired back?

**Nils Gilman** (2:21)
I think Wired is back. They're doing some of the best political reporting on tech and politics.

**Andrew McAfee** (2:25)
All right.

**Nils Gilman** (2:25)
Yeah, they're doing great stuff.

**Andrew McAfee** (2:26)
That's really good news.
Twenty years ish before Wired, there is this magazine called Omni that was Wired-ish. It also included sci-fi. It's where I came across William Gibson for the first time. But my mom heard about it or saw an issue or walked home and gave me this magazine. And my brain exploded because this was the thing that I was going to be focused on from that time forward.

**Nils Gilman** (2:53)
And I guess there's been discussions about AI since the 1950s, obviously. But when did you start tuning into AI specifically as something that you thought was going to be relevant, not just as an interest, but also as a matter of your work?

**Andrew McAfee** (3:07)
That happened right around the time that Erik Brynjolfsson and I started working on the book that became The Second Machine Age. Because I'm going to tell you things you already know. There was a very long AI winter. There was this initial burst of enthusiasm around AI, starting, I think you're right, in the 50s and then through the 60s. And people were making these very confident predictions that soon we'll have a chess computer that can beat any human grandmaster. People were saying that I think in the 60s, if not earlier.
And then it's kept on not happening.
And most of the business technology ecosystem turned away from AI with a couple of very small exceptions and started doing other things. Business intelligence and the internet came along. And there are all these other waves of stuff to get interested in with the business of computation.
And then kind of out of the blue, machine learning became unignorable and really powerful. The Landmark event, I think, was in 2012, when deep learning demonstrated that it was better at categorizing images than all these special hand-tuned algorithms that people had been working on for a while. And that was kind of a holy cow moment. And Erik and I were already part of this group, Erik was at MIT then, of economists and economics-adjacent people who were interested in AI. And then computer scientists who were interested in the economic implications of AI. I always remember, we'd sit across the table from each other. And I had the strong impression that both sides of the table were looking at the other one going, okay, you tell us what's going on. Because this is weird. It was kind of unanticipated and it feels like it's going to be a big deal. And then that got a booster shot, more like, you know, like a near-overdose level booster shot, when generative AI became unignorably powerful and amazing. And is it the third or third anniversary of CHAT GPT?