“The Jetsons” premiered in 1962. And based on the internal math of the show, George Jetson, the dad, was born in 2022. He’d be a toddler right now. And we are so far away from the world that show imagined. There were a lot of future-trippers in the 1960s, and most of them would be pretty disappointed by how that future turned out. So what happened? Why didn’t we build that future? The answer, I think, lies in the 1970s. I’ve been spending a lot of time studying that decade in my work, trying to understand why America is so bad at building today. And James Pethokoukis has also spent a lot of time looking at the 1970s, in his work trying to understand why America is less innovative today than it was in the postwar decades. So Pethokoukis and I are asking similar questions, and circling the same time period, but from very different ideological vantages. Pethokoukis is a senior fellow at the American Enterprise Institute, and author of the book “The Conservative Futurist: How to Create the Sci-Fi World We Were Promised.” He also writes a newsletter called Faster, Please! “The two screamingly obvious things that we stopped doing is we stopped spending on science, research and development the way we did in the 1960s,” he tells me, “and we began to regulate our economy as if regulation would have no impact on innovation.” In this conversation, we debate why the ’70s were such an inflection point; whether this slowdown phenomenon is just something that happens as countries get wealthier; and what the government’s role should be in supporting and regulating emerging technologies like A.I.

Back in 2018, Dario Amodei worked at OpenAI. And looking at one of its first A.I. models, he wondered: What would happen as you fed an artificial intelligence more and more data? He and his colleagues decided to study it, and they found that the A.I. didn’t just get better with more data; it got better exponentially. The curve of the A.I.’s capabilities rose slowly at first and then shot up like a hockey stick. Amodei is now the chief executive of his own A.I. company, Anthropic, which recently released Claude 3 — considered by many to be the strongest A.I. model available. And he still believes A.I. is on an exponential growth curve, following principles known as scaling laws. And he thinks we’re on the steep part of the climb right now. When I’ve talked to people who are building A.I., scenarios that feel like far-off science fiction end up on the horizon of about the next two years. So I asked Amodei on the show to share what he sees in the near future. What breakthroughs are around the corner? What worries him the most? And how are societies that struggle to adapt to change and governments that are slow to react to them supposed to prepare for the pace of change he predicts? What does that line on his graph mean for the rest of us? This episode contains strong language.