Occupational Information Network

And labor's overall share of the economy shrinks from about 59% today down to 45% in that extreme scenario.

The model itself is built from bundles of tasks within jobs using the Department of Labor's own O-Net job data, and it was reviewed by well-known economists Dan Akimoglu and David Autour.

If I mispronounced your name, I'm so sorry.

My take here, here's the headline most people will miss.

It lets anyone plug in their own assumptions about AI capability and adoption and see the resulting economic projections through 2030 for things like GDP, unemployment, wages, labor share of income.

And the model actually breaks every U.S. job down into task bundles using the federal government's own O-Net occupation data.

Then it simulates how AI augments or automates or creates tasks inside of each one.

And it comes packaged with a survey of nearly 11,000 Americans and three built-in scenarios.

It expands human capabilities and creates entirely new work.

And they tracked this using Onet data, right?

Yeah.

They identified entirely new job titles that didn't exist before.

Right.

But if you look at O*NET, uh, O*NET ONLINE, right, um, which draws from the Bureau of Labor Statistics, uh, for a variety of different types of roles, right? You will, you will find all this information about the types of skills needed, the type of education, training, but then those motivating factors, personality types, that type of stuff will fall into there.

So why not also add into here- Before you post a job description, right, what make up, what does that, what does that persona look like?

Yeah.