Dario Amodei

Even legendary programmers are increasingly describing themselves as behind.

The pace may if anything continue to speed up as AI coding models increasingly accelerate the task of AI development.

To be clear, speed in itself does not mean labor markets and employment won't eventually recover, it just implies the short-term transition will be unusually painful compared to past technologies since humans and labor markets are slow to react and to equilibrate.

Cognitive breadth.

As suggested by the phrase, country of geniuses in a data center, AI will be capable of a very wide range of human cognitive abilities, perhaps all of them.

This is very different from previous technologies like mechanized farming, transportation, or even computers.

This will make it harder for people to switch easily from jobs that are displaced to similar jobs that they would be a good fit for.

For example, the general intellectual abilities required for entry-level jobs in, say, finance, consulting, and law are fairly similar, even if the specific knowledge is quite different.

A technology that disrupted only one of these three would allow employees to switch to the two other close substitutes, or for undergraduates to switch majors.

but disrupting all three at once, along with many other similar jobs, may be harder for people to adapt to.

Furthermore, it's not just that most existing jobs will be disrupted.

That part has happened before.

Recall that farming was a huge percentage of employment.

But farmers could switch to the relatively similar work of operating factory machines, even though that work hadn't been common before.

By contrast, AI is increasingly matching the general cognitive profile of humans, which means it will also be good at the new jobs that would ordinarily be created in response to the old ones being automated.

Another way to say it is that AI isn't a substitute for specific human jobs but rather a general labor substitute for humans.

Slicing by cognitive ability

Across a wide range of tasks, AI appears to be advancing from the bottom of the ability ladder to the top.

For example, encoding our models have proceeded from the level of a mediocre coder to a strong coder to a very strong coder.

We are now starting to see the same progression in white-collar work in general.