George Hahn

This is Jevons' paradox.

When a resource becomes dramatically cheaper to use, we don't use less of it.

We find a million new uses for it.

That sounds painless?

Keep listening.

In March, Anthropic published the most detailed empirical map yet of AI's penetration into the labor market, finding that in business and finance occupations, AI could theoretically cover 94% of tasks tied with occupations in computers and math.

Pain is on the horizon, as tasks that can be automated will be automated during the next downturn.

But the tasks professionals perform have never been fixed, according to Eldar Maximov, an accounting professor at Arizona State University.

After the release of the first electronic spreadsheet in 1979, people predicted accountants would face mass unemployment.

Instead, after adjusting for population growth, the number of accountants increased 4x over the next 40 years.

In every major occupational group that adopted computers heavily, employment grew faster than in groups that did not, Maximov wrote.

Computers eliminated specific tasks within jobs, but the resulting cost reductions created so much new demand that the occupations expanded overall.

Looking at AI, he concludes that the future of every knowledge profession hinges on a single question.

Is human demand for analysis, oversight, and assurance elastic?

I believe it is.

Case in point, computer programmers.

They're coding less and thinking bigger, according to journalist Clive Thompson, who interviewed more than 70 programmers in Silicon Valley and at small firms across the U.S.

As he noted, a coder is now more like an architect than a construction worker.

One executive Thompson interviewed put it this way,

I have never met a team at Google who says, you know, I'm out of good ideas.