Dr. Emilia Javorsky

You know, this is a national crisis, our healthcare crisis at the moment and our spending on healthcare.

Like, why are we spending all that money where AI could do those administrative tasks and that money could be routed back to actually taking care of people and giving them care or lowering the costs of care?

So I think there are ways we can reimagine healthcare with AI, with a better system, with better incentives that get us where we actually want to go.

But we have to be proactive and mindful about that.

We can't just, you know, let AI loose in the world that we have because we're just going to get more of the things that we already have, which we know in healthcare is not things that we want.

Yeah.

I think step one in making progress in this domain is the data piece of the story, measurement and data.

How do we better measure our biology?

How do we better capture and understand what cancer is, what's happening in an individual?

And collecting that data with the state of the science that we have at scale.

And an example that I think is really prolific is

has been the work that has happened in the United Kingdom with their UK biobank project.

So this was a project where they followed 500,000 people, and they're still going, over 20-plus years using actual sort of modern, state-of-the-art measurement techniques.

So this isn't the simple blood test when you go to your doctor and you get the paper readout and there's like 30 things on it.

This is measuring thousands of things in the body.

This is taking all kinds of imaging of the body.

And we're starting to see these headlines like AI can predict Alzheimer's 10 years earlier, right?

And that is actually a story of just normal AI machine learning methods applied to this prolific data set that has come out and required decades of investment.

and actually measuring just the baseline.

Like what does healthy look like?