Peter McCrory

To become an expert economist, you need to

To get to the frontier, you need to spend many years sort of getting that narrow expertise.

But in principle, it might be the case that these large language models, they've read the corpus of human knowledge.

They can maybe span the space where new ideas, productive ideas, both for scientific applications and for business applications, that's where they exist.

So I think that is like a pressing question to which we don't currently...

analyze in our report and sort of something that's very much on my mind.

I think another way to think about it is, again, another shout out to Ben Jones.

This paper from fall of late last year

where he explores this idea of what if there are tasks in the innovation process that are not automated by AI?

And there you have this tension where it might be the case that you have unbelievably capable artificial intelligence.

So the depth of capability is just like growing immensely.

But if it is constrained to a subset of tasks that are crucially involved in the innovation process, that will limit the extent to which you could have takeoff and the extent to which productivity growth might rise above average.

2%, 3%.

Anything higher would be like historically unimaginable in many ways.

And I think we have to think about these things with some level of humility.

The long 20th century from 1870 to the end of the early 2000s was a

You know, a period of immense technological transformation, immense automation, the decline in the share of workers in agriculture from above 80% to around 3% today.

And if you look over the long sweep of history in the U.S., at least over that time, it's about 2% points real GDP growth each year.

So I think the future is very uncertain.

And again, that's like the big motivation that I have in doing this work is like trying to help us, others, policymakers, researchers to see a bit further into the future, to see a bit more clearly.