Thank you for this comment! I’ll make reply to different points in different comments.

But then the next point seems very clear: there’s been tons of population growth since 1880 and yet growth rates are not 4x 1880 growth rates despite having 4x the population. The more people → more ideas thing may or may not be true, but it hasn’t translated to more growth.

So if AI is exciting because AIs could start expanding the number of “people” or agents coming up with ideas, why aren’t we seeing huge growth spurts now?

The most plausible models have *diminishing returns* to efforts to generate new ideas. In these models, you need an exponentially growing population to sustain exponential growth. So these models aren’t surprised that growth hasn’t increased since 1880.

At the same time, these same models imply that if increasing output causes the population to increase (more output → more people), then there can be super-exponential growth. This is because the population can grow *super-exponentially* with this feedback loop.

So my overall opinion is that it’s 100% consistent to think:

The increased population of the last 100 years didn’t lead to faster growth

If AGI means that more output → more people, growth will accelerate.

This is an interesting idea. It wasn’t a focus of my work, but my loose impression is that when economists have attempted to correct for these kinds of problems the resulting adjustment isn’t nearly large enough to make Roodman’s model consistent with the recent data. Firstly, measurements of growth in the 1700s and 1800s face the same problem, so it’s far from clear that the adjustment would raise recent growth relative to old growth (which is what Roodman’s model would need). Secondly, I think that when economists have tried to measure willingness to pay for ‘free’ goods like email and social media, the willingness is not high enough to make a huge difference to GDP growth.