If an obscure 1980s paradox is any guide, AI may be about to hit a huge tipping point

There’s an old joke among economists that goes like this: “You can see the computer age everywhere but in the productivity statistics.” I didn’t say it was a funny joke. But when labor economist Robert Solow originally wrote those words in 1987 , they were certainly true. Personal computers, corporate mainframes, and the first vestiges of the modern internet were all anyone could talk about. Yet productivity wasn’t budging. These whizzy technologies, in short, weren’t earning anyone any money. The phenomenon became known as Solow’s Paradox. Of course, we all know how that story ended. By the mid-1990s, productivity was on a tear, and tech was making lots of people fabulously wealthy. And (despite a subsequent crash and recovery), tech is now the linchpin of the modern economy. Today, AI is following a similar path. And new data suggests that a similarly massive productivity–and wealth–tipping point may be just around the corner. Old paradoxes Since generative AI surged into mainstream