Substack version here:
https://andreinfante.substack.com/p/when-will-ai-transform-the-economy

A caricature of a common Twitter argument:

”Hey it seems like language models can do a lot of humanlike cognitive tasks, look at this impressive example! That seems like something that would transform the economy.”

“Well, smart guy, these things have been out for a couple of years now. Why isn’t the economy transformed yet?”

This does strike me as a little bit mysterious. The models can do impressive things- solving programming tasks, tackling math and logic puzzles, and answering detailed scientific questions. The median human can barely do these things at all, and the best language models can often do them very well. This seems like an indicator that language models should be well positioned to replace human knowledge workers in droves.

However, even industries that have adopted language models aggressively (e.g. software engineering) are not seeing huge changes to employment or productivity so far. Even accounting for lagging indicators, many early predictions of immediate economic transformation and mass unemployment have not been borne out.

Anecdotally, if I throw a random bite-sized problem at AI, it often totally knocks my socks off (especially taking speed into account). But if I try to use it to solve real problems in my actual job for any length of time, the shine starts to come off a little bit. As a software engineer, these tools genuinely help me (especially in areas where I am less proficient, like web development). But they are not revolutionary. I am not ten times more productive.

One way to relax this apparent tension is to reframe the issue in terms of ceilings and floors. The models have quite high intelligence ceilings (the greatest complexity of task they can sometimes do), better than most humans. However, their intelligence floors (the simplest task they sometimes fail at) are fairly low: they make mistakes that you would expect from a young child, or someone with a cognitive impairment. This combination makes them impressive, but unreliable.

This combination is pretty rare in humans! Human ceilings and floors tend to only be so far apart. I think this is one of the reasons why these things are so polarizing. People latch onto either the bottom or top end of their performance distribution and use it to either dismiss them as shallow babblers or o...

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