39. Aicha Evans Wants You to Take Your Eyes Off the Road

Steven Levitt (0:05)

My guest today, Aicha Evans, has followed an improbable path. Born in Senegal, trained as an engineer, she leads a billion-dollar company called Zoox. That's Z-O-O-X. Zoox is making a radical bet on the future of driving. They're developing a fleet of robotaxis that will pick up and drop off riders on demand. But one glimpse of these cars, and you will know what I mean by radical.

No steering wheel, no front or back seat, just a big open rectangle with two bench seats facing each other.

They're only testing these vehicles, but I want to find out how long it will be before they're functional, so I can buy one.

SPEAKER_2 (0:43)

Welcome to People I Mostly Admire with Steve Levitt.

Steven Levitt (0:50)

Have you noticed that I almost never have CEOs as guests on the show? That's because my experience with CEOs is that they won't say publicly what they actually believe, they just spout the company line. I'm making an exception today because I've heard Aicha Evans is different, and we're about to find out whether or not that's really true. Just a heads up, at a few points in this episode, you'll be able to tell I'm wrestling with a head cold. I'm feeling better, but thanks in advance for bearing with me.

Do you have the sense that autonomous driving has turned out to be a tougher problem to solve than the engineers and data scientists expected? I feel like I've been hearing for a decade that we were right on the cusp of fully autonomous vehicles.

Aicha Evans (1:33)

I absolutely think so. As an industry, we've underestimated the problem. But I'm one of those optimists. I actually think that's a good thing.

Because when you have a generational challenge and opportunity, if at the beginning of the journey, you start talking about how complicated and difficult it's going to be, you might not try. You might not get going. But progress is definitely being made. And I'm glad we all got onto the journey. I consider this to be basically something that's inevitable. It's a matter of time and it's really going to change a lot of things in our lives, and environment, and cities, and how we do things, and how people move around.

Steven Levitt (2:11)

Yeah. If this doesn't happen, then I think our entire vision of what the future is like is very different than what we're imagining. So first, maybe you could explain what the strategy is that Zoox is following, and how you fit into the broader schema of autonomous vehicles.

Aicha Evans (2:28)

Yeah. So for Zoox, it's really we're a transportation company. We're setting out to reinvent personal transportation to make it safer, cleaner, and more enjoyable. We basically have a fleet of fully electric, fully autonomous vehicles that are available on demand when you need them, and when you don't need them, somebody else is using them, so it's extremely efficient from that standpoint. We handle the maintenance, the charging, the driving. You basically say, I want to go from point A to point B.

We show up, sliding doors, step in, sit down, buckle up, push start, personalize your space a little bit, and by the time we drop you off, we are picking up another passenger. So we are really all about riders and people who need to be transported from point A to point B, and that's a very different model for most. It's not like mobility on demand is a new concept, right? We have a couple of companies in the United States that are providing it today, but it's with a human driver that is driving a passenger car.

Steven Levitt (3:33)

It seems to me that there are three very different types of barriers that stand in the way of fully autonomous vehicles.

One is the technical challenge, the science and engineering of solving a really hard problem. The second barrier is human psychology, getting humans to trust the technology and to change their habits.

The third is politics and regulation, because I think even if you have a great technology that people would use, powerful interests are going to try to stand in the way of actually letting us put those into practice. I was hoping you could just run through those one by one, starting with the technical side.

Aicha Evans (4:10)

Just getting a vehicle to drive is not that difficult, but getting it to drive amongst other human drivers and being able to follow its trajectory, get to the right place, follow not just the rules but the norms, and then predict and react to what other drivers will do, which are human drivers. And so now with the advances in robotics, in AI, and also in general in compute, we do have the foundational element. It's now about testing, having quantifiable ways to say, is it safe and is it doing the right thing?