Mary Daly

In productivity numbers,

especially when they're happening in what I would think of as real time, it's very challenging to assess or draw it back to exactly what the factors are that have shaped it.

You know, in fact, people still don't agree on what happened in the 90s all the time if you look at research.

So it's just something to keep in mind.

So then what you do, what any good economist or person, any industry person would do is they'd say,

Well, what am I seeing?

What am I seeing?

And so right now, while we can't find it in the macro studies that would do very sophisticated empirical econometrics and ask the questions, how much of this is AI?

We still can see that there's something going on there.

The question isn't, is it happening?

The question is,

how long will it persist?

And so clearly something's happening in the economy, but if you make a series, to go back to your question about productivity, if you make a series of one-time adjustments, so say you automate a production line,

or you use AI to help in loan application process.

You save money once.

You don't save money forever.

I mean, you keep saving that money, but you don't get growth out of that.

You don't get productivity growth.

You get one-time adjustments to the level of productivity of your employees or your process.

So what we're looking for is a technology to give us consistently good