For the past few years, artificial intelligence has been touted as an earth-shattering advancement for humanity. Noah Smith argues that, while this new technology has reshaped our habits in many ways, it has yet to shatter our current reality.

Not a lot of people expected that AI would come for the mathematicians before it came for the truck drivers, but it did. The other day, an AI model disproved the Jacobian Conjecture—an 87-year-old open problem that human mathematicians had struggled to solve. The greatest living human mathematician, Terence Tao, turned to AI to help him understand the solution. Around the same time, AI solved a very important open question in quantum cryptography. Solving Erdos problems has now become almost child’s play for the best AI models. And this is the worst AI will ever be at math. Model capabilities, and the amount of compute available, both continue to increase at rapid rates. (Meanwhile, long-distance trucking employment is slightly higher than it was a decade ago.)

We don’t expect mathematicians to actually lose their jobs en masse, of course. But it’s becoming clearer and clearer that humankind has invented machines that are smarter than we are. Intelligence isn’t defined for machines the same way it is for humans—AI’s capabilities are spiky in different ways than ours—but it’s undeniable that the technology is improving rapidly in every domain of cognitive capability. It’s still possible to find some mental tasks that humans are better than machines at, but those final advantages tend to disappear almost as quickly as we can identify them. “AGI”, or “ASI”, or whatever you want to call it, is certainly here.

And yet… the world remains much the same. In lots of sci-fi books, as soon as artificial superintelligence arrives, it bootstraps itself to even more godlike intelligence in an explosive “singularity” that rapidly transforms the entire physical universe. Lots of people, especially “AI safety” and “effective altruist” types, expected things to play out basically the same way in reality. But looking around, not much has changed since we entered the intelligence explosion. There’s a huge data center boom, and most people use AI on a daily basis, but we still live basically the same lives—driving to work or taking the train, sitting in front of a computer, scrolling on our phones, collecting a paycheck. People are staying in their jobs longer, but employment hasn’t been disrupted in a significant way :

Meanwhile, we’ve had decently robust productivity growth, but nothing really amazing :

It seems possible that humans are simply incredibly specialized in a few types of cognitive tasks—extracting patterns from sparse data, synthesizing various patterns into “intuition” and “judgement”, and communicating those patterns in language—and that we’ve basically approached the theoretical maximum in those narrow areas… That would explain why AI has gotten much better at things like math and coding and forecasting over the last year but why the basic chatbot interface doesn’t seem much more “intelligent.” It would also explain why when you talk to Terence Tao about math, it’s like talking to a superhuman, but when you talk to him about where to get lunch or which movies are the best, he’ll just sound like a fairly smart normal dude. AI will eventually get better than Tao at math… but it may never get much better than the most thoughtful, eloquent humans at deciding where to get lunch or recommending movies. It may simply not be mathematically possible to get much better than we already are at that sort of thing.

Why would intelligence top out like this ? Well, if we think of intelligence as the ability to extract information from data, then even an infinitely advanced model endowed with infinite compute will be limited by the fact that there’s a limited amount of information that can be extracted from the data.

For one thing, data itself is in limited supply. You can’t transform the world unless you can (in some generalized sense) understand it, and you can’t understand the world unless you can measure it, and our ability to measure the world is inherently limited and finite.