In this episode, Byron and Esther talk about intelligence, jobs, her experience in being a backup cosmonaut and more.
Byron Reese: Today, our guest is Esther Dyson. Esther Dyson is a living legend. She has been an angel investor, and sits on the boards of a number of companies. She is also a best-selling author, a world citizen, and a backup cosmonaut for the Russian Space Program. Now, she serves as the Executive Founder for a non-profit called Way to Wellville. Welcome to the show, Esther.
Esther Dyson: Delighted to be here.
Let’s start with that; that sounds like an intriguing non-profit. Can you talk about what its mission is, and what your role therein is?
Yeah. My role is, I founded it. The reason I founded it, was a question, which was… As I was an angel investor, and doing tech, and getting more and more interested in healthcare, and biotech, and medicine, I also had to ask the basic question; which is: “Why are we spending so much money and countenancing so much tragedy by fixing people when they’re broken, instead of keeping them healthy and resilient, so that they don’t get sick or chronically diseased in the first place?”
The purpose of Way to Wellville is to show what it looks like when you help people stay healthy. I could go on for way too long, but it’s five small communities around the US, so you can get critical mass in a small way, rather than trying to reshape New York City or something.
The basic idea is that this happens in the community. You don’t actually need to experiment and inspect people one-by-one, but change the environment they live in and then look at sort of the overall impact of that. It started a few years ago as a five-year project and a contest. Now, it’s a ten-year project and it’s more like a collaboration among the five communities.
One way AI is really important is that in order to show the impact you’ve had, you need to be able to predict pretty accurately what would’ve happened otherwise. So, in a sense, these are five communities, the United States is the control group.
But, at the same time, you can look at a class of third graders and do your math, and say that one-third of these are going to be obese by the time they’re sixteen, 30% will have dropped out, 10% will be juvenile delinquents, and that’s simply unacceptable. We need to fix that. So, that’s what we’re doing.
We’ll get to the AI stuff here in a moment but I’m just curious, how do you go about doing that? That seems so monumental, as being one of those problems like, where do you start?