Jun 3, 2026 · 1 hr 39 min · 13 segments
Danielle Wood is an Australian economist and the current chair of the Australian Productivity Commission. Had a lot of fun chatting with Dani about how she's making sense of AI and its implications…
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So first question is, I was catching up with a friend on the weekend, and we were talking about how big of a deal AI is gonna be.
And I said, and when I use subjective probabilities, I'm always being semi-ironic, but I said I, I give AI a kind of 90 to 95% probability of being at least as big as the internet, and maybe a 20 to 40% probability of being at least as big as the Industrial Revolution, by which I mean that it could lead to a, a regime shift in the underlying total factor productivity growth rate.
So I don't know, maybe the growth rate moves to, like, three to five times the historical average in the same way that through the Industrial Revolution it went from nearly 0% to modern rates of about 1% or above.
So 90 to 95% probability of being at least as big as the internet, 20 to 40% probability of being at least as big as the Industrial Revolution.
Uh, look, I mean, I think that is the right way to think about the kind of, uh, plausible set of outcomes.
I mean, we, you know, we think it will have a, a meaningful impact on productivity.
It's, it, it's, you know, general purpose technology, uh, like the kind of previous waves.
The internet was one, um, you know, ICT more generally, you know, electricity, steam, you know, all of those things have, through history, fundamentally kind of transformed the economy and touched different sectors.
The kind of conservative view, which is probably your internet parallel, is, hey, there's just a whole lot of different tasks that it can do more efficiently.
Uh, and we did this exercise, um, for some work we did for the government last year on productivity that said, "Okay, well, look at-- let's look at the evidence on these sort of task-specific efficiencies.
Let's look at, um, you know, the number of tasks across the economy that might be affected." Uh, and you get a kind of, "Well, it could improve labor productivity, uh, by about 4% over a decade." Um, so that's, like, pretty meaningful.
Um, you know, it would actually be almost a, a doubling of, of where we've been over the past decade, albeit from quite a low-
Um, the, you know, the Industrial Revolution parallel, um, your three to five times total factor productivity, uh, is more of a fundamental change than that.
And I think, you know, you start to get that sort of scale of impact in a world where AI actually changes the innovation process itself.
So we know that over time it's innovation that, that drives total factor productivity.
... innovation, if it starts to, um, you know, speed up the rate at which we, you know, find new goods or new ways of doing things or ways of solving social problems, then you're in that kind of extraordinary world that you're talking about.
I don't know if I'll, uh, be as, uh, specific as, as you have been, but you know, I think that is a world that we could be in with this technology.
So first question is, I was catching up with a friend on the weekend, and we were talking about how big of a deal AI is gonna be.
And I said, and when I use subjective probabilities, I'm always being semi-ironic, but I said I, I give AI a kind of 90 to 95% probability of being at least as big as the internet, and maybe a 20 to 40% probability of being at least as big as the Industrial Revolution, by which I mean that it could lead to a, a regime shift in the underlying total factor productivity growth rate.
So I don't know, maybe the growth rate moves to, like, three to five times the historical average in the same way that through the Industrial Revolution it went from nearly 0% to modern rates of about 1% or above.
So 90 to 95% probability of being at least as big as the internet, 20 to 40% probability of being at least as big as the Industrial Revolution.
Uh, look, I mean, I think that is the right way to think about the kind of, uh, plausible set of outcomes.
I mean, we, you know, we think it will have a, a meaningful impact on productivity.
It's, it, it's, you know, general purpose technology, uh, like the kind of previous waves.
The internet was one, um, you know, ICT more generally, you know, electricity, steam, you know, all of those things have, through history, fundamentally kind of transformed the economy and touched different sectors.
The kind of conservative view, which is probably your internet parallel, is, hey, there's just a whole lot of different tasks that it can do more efficiently.
Uh, and we did this exercise, um, for some work we did for the government last year on productivity that said, "Okay, well, look at-- let's look at the evidence on these sort of task-specific efficiencies.
Let's look at, um, you know, the number of tasks across the economy that might be affected." Uh, and you get a kind of, "Well, it could improve labor productivity, uh, by about 4% over a decade." Um, so that's, like, pretty meaningful.
Um, you know, it would actually be almost a, a doubling of, of where we've been over the past decade, albeit from quite a low-
Um, the, you know, the Industrial Revolution parallel, um, your three to five times total factor productivity, uh, is more of a fundamental change than that.
And I think, you know, you start to get that sort of scale of impact in a world where AI actually changes the innovation process itself.
So we know that over time it's innovation that, that drives total factor productivity.
... innovation, if it starts to, um, you know, speed up the rate at which we, you know, find new goods or new ways of doing things or ways of solving social problems, then you're in that kind of extraordinary world that you're talking about.
I don't know if I'll, uh, be as, uh, specific as, as you have been, but you know, I think that is a world that we could be in with this technology.
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